

Dialogue & Discourse 12(2) (2021) 1–37 doi: 10.5210/dad.2021.201

Discourse Relations and Connectives in Higher Text Structure

Lucie Poláková POLAKOVA@UFAL.MFF.CUNI.CZ
Institute of Formal and Applied Linguistics
Faculty of Mathematics and Physics, Charles University

Jiří Mírovský MIROVSKY@UFAL.MFF.CUNI.CZ
Institute of Formal and Applied Linguistics
Faculty of Mathematics and Physics, Charles University

Šárka Zikánová ZIKANOVA@UFAL.MFF.CUNI.CZ
Institute of Formal and Applied Linguistics
Faculty of Mathematics and Physics, Charles University

Eva Hajičová HAJICOVA@UFAL.MFF.CUNI.CZ

Institute of Formal and Applied Linguistics
Faculty of Mathematics and Physics, Charles University

Editor: Vera Demberg

Submitted 12/2020; Accepted 06/2021; Published online 07/2021

Abstract

The present article investigates possibilities and limits of local (shallow) analysis of discourse co-
herence with respect to the phenomena of global coherence and higher composition of texts. We
study corpora annotated with local discourse relations in Czech and partly in English to try and find
clues in the local annotation indicating a higher discourse structure. First, we classify patterns of
subsequent or overlapping pairs of local relations, and hierarchies formed by nested local relations.
Special attention is then given to relations crossing paragraph boundaries and their semantic types,
and to paragraph-initial discourse connectives. In the third part, we examine situations in which
annotators incline to marking a large argument (larger than one sentence) of a discourse relation
even with a minimality principle annotation rule in place. Our analyses bring (i) new linguistic
insights regarding coherence signals in local and higher contexts, e.g. detection and description of
hierarchies of local discourse relations up to 5 levels in Czech and English, description of distri-
bution differences in semantic types in cross-paragraph and other settings, identification of Czech
connectives only typical for higher structures, or the detection of prevalence of large left-sided ar-
guments in locally annotated data; (ii) as another type of contribution, some new reflections on
methodologies of the approaches under scrutiny.
Keywords: local and global discourse coherence, Prague Discourse Treebank 2.0, discourse con-
nectives, hierarchies, paragraphs

1. Introduction

In coherence-oriented discourse studies, the recognition of the distinction between local and global
coherence dates back to the 1980’s and one of the most compelling ways of its explanation is that
“the main purpose of global coherence relations is to help eliminate locally coherent nonsense texts”
(Unger, 2006, Samet and Schank, 1984). According to them, global coherence is the connectivity

©2021 Lucie Poláková, Jiří Mírovský, Šárka Zikánová and Eva Hajičová

This is an open-access article distributed under the terms of a Creative Commons Attribution License
(http ://creativecommons.org/licenses/by/3.0/).


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

between the main events of the text (scripts, plans and goals) and the global relations hold in-
dependently of the local coherence relations between discourse segments. In automatic discourse
processing, the local and the global coherence models are also known as shallow and deep discourse
analyses/parsing, respectively (Prasad et al., 2010). Both types of approaches deal with determina-
tion and description of semantic and pragmatic relations between individual text units but they differ
in the focus of the analyses and the methodology.

Local coherence models proceed bottom-up, from the smallest discourse units within a single
sentence (clauses, even nominalized events, states etc.) and across the sentence boundary. Emphasis
is put on the description of semantico-pragmatic relations between every two consecutive units and
on the identification of lexical cues anchoring these relations (mostly discourse connectives; where
there is no such surface cue, the relation is called implicit). The coherence analysis in this way
describes how every discourse unit is related to the previous one, there are no hierarchies postulated
and no claims about the shape of the overall structure of the analyzed documents. The advantage
of local discourse analyses is their easy applicability in annotation and shallow parsing (looking
for surface cues, connectives and other markers), given the usability across different languages and
relatively high reliability (e.g. via inter-annotator agreement). As far as language resources aiming
at formalized linguistic description of discourse coherence are concerned, internationally, there is a
range of corpora annotated for local coherence relations in different languages. They mostly follow
the Penn Discourse Treebank (PDTB) annotation style (Prasad et al., 2008, Prasad et al., 2019),
compare 2.2. There exists even a multilingual corpus with local discourse annotations in the PDTB
style of parallel texts in six languages (Zeyrek et al., 2019).1 For Czech, there is a publicly available
large corpus of local discourse annotation, the Prague Discourse Treebank 2.0 (PDiT 2.0; Rysová
et al., 2016), see Section 3. This resource has been developed by the Prague discourse group since
2009 and thus naturally represents the point of departure for this study.

Global coherence models, on the contrary, proceed top-down, from the text as a communicative
whole, and postulate a hierarchically interconnected structure of smaller and larger units. These
models usually capture each document as a single continuous graph representation with specific
properties and constraints on the relations (e.g. tree-like graphs). This concept has a strong po-
tential in the possibility to demonstrate the composition of smaller blocks of the text, as well as
to identify more general and more important text contents and relations between them. For global
annotations, there are far less projects, compare Section 2, and so far, there is no such project for
Czech data. However, global coherence modeling (often in addition to local coherence models),
apart from its straightforward application in automatic coherence evaluation (Feng et al., 2014, Lin
et al., 2011) can significantly contribute to other NLP tasks, such as summarization (Zhang, 2011),
topic identification (Pons-Porrata et al., 2007), text generation (Kiddon et al., 2016), textual entail-
ment (Hagege and Jacquet, 2014) and others.

In this study, we examine the distributions, properties and mutual settings of local discourse
relations in order to reveal possible patterns of higher discourse structuring and signs of global
discourse coherence. Our research question is: Is global coherence signaled by the same types of
language devices as the local one or can we reveal some differences by studying various phenomena
in locally annotated data?

The different types of local discourse relations and their mutual settings that we analyze in this
study are represented in Example 1 and Figure 1 which outlines discourse annotation in the Czech

1. The most exhaustive list of discourse-annotated corpora of any type was collected within the TextLink initiative and
can be accessed from this url: http://www.textlink.ii.metu.edu.tr/corpus-view

2

http://www.textlink.ii.metu.edu.tr/corpus-view


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

If the new limits
could be prepared
sooner

they will probably only be
issued as another amend-
ment to the old law directive

So it seems

that the processors are
in no hurry with new limits

Yet there is hunger
for new limits

condition
connective: If
range: 0->0

reason-result
connective: So
range: 0->0

concession
connective: Yet
range: 0->0

S1 S2 S3

Figure 1: An annotated example of an intra-sentential relation (condition), inter-sentential relation
within a paragraph (reason-result) and a cross-paragraph relation (concession) from the
Prague Discourse Treebank 2.0. Nodes represent individual clauses, root nodes refer
to individual sentences, semantic types of discourse relations are highlighted in orange,
connectives in green.

PDiT 2.0. The example demonstrates an intra-sentential relation, an inter-sentential relation within
a paragraph and a cross-paragraph relation. Also, a hierarchical structure (a nested relation, i.e. a
relation fully included within an argument of another relation) is shown by this example text.

(1) (S1) If the new limits could be prepared sooner, they will probably only be issued as another
amendment to the old law directive. (S2) So it seems that the processors are in no hurry with
new limits.
[Paragraph boundary]
(S3) Yet there is hunger for new limits.

Czech original: (S1) Pokud by se podařilo nové limity připravit dříve, budou vydány zřejmě jen jako
další novela směrnice starého zákona. (S2) A tak se zdá, že zpracovatelé s novými limity nespěchají.
[Paragraph boundary]
(S3) Přitom po nových limitech je hlad.

Within the sentence (S1), there is an intra-sentential relation of condition signaled by the connective
pokud [if]. Its two arguments are the two clauses in this sentence. The whole sentence (S1) is
a left-sided argument of an inter-sentential reason-result relation anchored by a tak [so]. The if -
relation is a subset of so-relation, they are forming a hierarchical structure. These two sentences
belong to a single paragraph and the two mentioned discourse relations are local, intra-paragraph
relations. Sentence (S3) starts a new paragraph and it is attached to the preceding sentence (S2) by
a cross-paragraph inter-sentential concession relation with the connective přitom [yet]. In this case,
the cross-paragraph link is local, between adjacent sentences, but in other possible contexts, the
left-sided argument of the relation may span across several sentences or/and it can be non-adjacent.

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POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

1.1 Goals

The main goal of the present study is to systematically analyze existing local discourse annotations
of Czech, and partly English, for possible signs of higher/global discourse structure. The analysis
shall serve as springboard for a planned global coherence annotation of Czech, similarly as the deep-
syntactic layer was informative for the analysis of local coherence relations (Mírovský et al., 2012).
An underlying assumption is that even the local annotation already displays such features of global
text structure. This assumption is based on our observations from locally annotated data so far: we
detected patterns like hierarchical organization of smaller and larger discourse relations, connectives
and other discourse cues operating between larger blocks of texts, long-distance relations, genre-
related patterns and so on. Also, we hypothesize that in a well-formed, coherent text, the paragraph
structure, as a main formal structuring device, must be mirrored in discourse relations and their
semantics in some way.

Corpus analyses of possible features of higher/global text structure in this study concern three
separate topics:

• The issues of structure, or “the shape” of a text: we investigate mutual configurations of dis-
course relations (pairwise) and their complexity within locally annotated texts of Prague Dis-
course Treebank 2.0. We identify and quantify the embeddings, overlappings and crossings
of relations, according to a similar study conducted by Lee et al. in 2006 on complexity of
discourse structure in the Penn Discourse TreeBank 2.0. Moreover, we look into hierarchies
local discourse relations can form. This research was previously published in Poláková and
Mírovský (2020). In this new version, we reflect on some feedback by our readers, explain
our previous findings in more detail and by more examples, give original Czech annotated
examples where they were originally left out due to space limitations, and, most importantly,
extend our analysis of hierarchies of nested relations by an analogous one for the English
annotations in the PDTB 3.

• The analysis of paragraph-initial connectives, relations they anchor and their respective dis-
course types (senses). This analysis is intended to reveal any possible differences between
(the majority of) relations within individual paragraphs and those cross-paragraph relations
in our data that have an explicit marking by a connective.

• The analysis of large arguments, more precisely, of relations with one or both arguments
larger than a single sentence, and their properties.

The article is structured as follows. In the second part of the Introduction, we specify the extent
of our study and define types of discourse relations with respect to their scope in the text structure.
Related research is mentioned in Section 2. Section 3 describes the data format and application
framework used in our study and presents the main data resources. Section 4 with four subsections
represents the core of the research and offers results of our study in four directions – (i) configu-
rations of pairs of discourse relations, (ii) hierarchies of nested discourse relations, (iii) paragraph-
initial senses and connectives, and (iv) relations with large arguments. Section 5 summarizes our
findings and offers some perspectives. Examples of texts with deep hierarchies of discourse rela-
tions can be found in two Appendices.

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DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

1.2 Theoretical Aspects and Definitions

For the descriptive purposes of this study, we need to terminologically distinguish several types of
coherence. Global coherence of a text refers to the coherence of a given document as a whole,
including all inner structure of its coherence relations of smaller and greater units. This inner struc-
ture is assumed to form hierarchies of smaller and larger relations. On the contrary, local coherence
refers to the “flat”, chain-like coherence of two minimal subsequent text units, as defined most elab-
orately in the PDTB 2 (Prasad et al., 2008) approach mentioned above. Further, we distinguish
coherence on a higher level, or the so-called higher text structure, which describes coherence re-
lations between/among larger text blocks, but not necessarily in a whole document. Typically, a
distinctive higher structure in a text is formed by (multi-sentential) lists and enumerations and it
often relates to genre rules or practises (e.g. in legal texts, instructions, recipes). Independently,
we also distinguish inter- or cross-paragraph coherence, that means, coherence relations between
individual paragraphs as integral units but also between smaller units belonging to two different
paragraphs. Coherence relations within individual paragraphs are then again referred to as local
relations, and they can be either intra- or inter-sentential, or belong to a higher structure, if made
up of larger units (more sentences).

Obviously, these categories are not rigorous and mutually exclusive, as already the very purpose
of this study – looking for global features in a locally annotated data – suggests. This gives rise to a
question, e.g., how to approach the relation of the last sentence of one paragraph to the immediately
following first sentence of the next paragraph, or, how to treat intra-sentential lists spanning across
several paragraphs. We will address these and further related issues further in Section 4.

A note should be made to the use of the term hierarchy in this study. Whereas we explore the
hierarchical organization of discourse relations as wholes, there also is another understanding of
hierarchy in discourse, in terms of the ways discourse units organize themselves based on criteria
such as their relative importance (nuclearity in Rhetorical Structure Theory). We do not address the
latter here.

2. Related Research

From the wide range of coherence theories which address a text/document as a structured whole
and offer some type of a formalized representation of this whole (e.g. Grosz and Sidner, 1986,
Hobbs, 1979, Asher and Lascarides, 2003, Wolf and Gibson, 2005),2 our approach is methodolog-
ically closest to the Penn Discourse Treebank and Rhetorical Structure Theory (RST), which are
introduced in more detail in the following sections.

2.1 Rhetorical Structure Theory

The Rhetorical Structure Theory (RST, Mann and Thompson, 1988) is one of the most influential
frameworks among the global coherence models. It was originally developed with the intention
to model text coherence in order to study computer-based text generation. The main principle of
RST is the assumption that coherent texts consist of minimal units, which are linked to each other,
recursively, through rhetorical relations and that coherent texts do not exhibit gaps or non-sequiturs
(Taboada and Mann, 2006). The RST represents the whole text document as a single (projective)

2. For a detailed classification of discourse approaches within the local/global space of coherence relations see Bateman
and Rondhuis (1997).

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POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

tree structure. Basic features of these structures are the rhetorical relations between two textual
units (smaller or larger blocks that are in the vast majority of cases adjacent) and the notion of
nuclearity. For the classification of RST rhetorical relations, a set of labels was developed, which
originally contained 24 relations, but the authors themselves add that it is an open set “susceptible
to extension and modification for the purposes of particular genres and cultural styles” (Mann and
Thompson 1988, p. 250). The type of a rhetorical relation is defined with respect to the author’s
intended effect on the reader together with the application of the principles of nuclearity.

The RST has gained great attention, it was further developed and tested, language corpora were
built with RST-like discourse annotation, such as for English the RST Discourse Treebank (RST-
DT, Carlson et al., 2003) and its extension RST-Signalling Corpus (Das et al., 2015), for German
(Stede and Neumann, 2014), Spanish (Da Cunha et al., 2011), Basque (Iruskieta et al., 2013) and
also for some other languages.

On the other hand, the framework was repeatedly criticized with regard to some of its theoretical
claims, above all, concerning the question of adequacy/sufficiency of representation of a discourse
structure as a tree graph.3 Linguistically, the strong constraints of a tree (no crossing edges, one
root, all the units interconnected etc.) gave rise to a search for counter-examples in real-world
texts. It was shown that not only adjacent text units exhibit coherence links and that there are even
cue phrases, which connect non-adjacent units and thus support the claim that a tree graph is too
restricted a structure for an adequate discourse representation (Wolf and Gibson, 2005). Therefore,
more complex graphs with crossings and overlaps should be adequate, which resulted in the creation
of the Discourse GraphBank (Wolf et al., 2005), a resource of the same texts annotated with the main
diverging principle of relaxing the tree-ness constraint.

On these grounds and in the same way like Lee et al. (2006), we try to demonstrate where the
local and global analytic perspectives meet and interact. Our analysis of Czech data thus contributes
new empirical material to the scientific debate on whether projective trees are descriptively adequate
to represent structure of texts (e.g. Marcu, 2000, Wolf and Gibson, 2005, Lee et al., 2008, Egg and
Redeker, 2010).

Additionally, there have been some RST-based studies investigating the distributions of rhetor-
ical relations on different levels of text, e.g. Williams and Reiter (2003), Liu and Zhang (2016).
Their research questions are similar to ours in the section on paragraph-initial relations and cues
4.3. The latter study introduces a RST-tree conversion to dependency trees with different levels of
granularity, with a node representing a clause, a sentence or a paragraph. They point out that most
rhetorical relations in the RST-DT treebank occur on all levels but with different percentages and
the two upper levels of discourse processes are more alike in many aspects, which are observations
that also follow from our local data analyses (4.3).

2.2 Penn Discourse Treebank

The Penn Discourse Treebank (PDTB) represents a lexically based, local model of discourse. Its
analysis of discourse relations consists primarily in finding and analyzing lexical cues of discourse
coherence as “anchors” of discourse relations. Such a cue, a discourse connective, is defined as
a discourse-level predicate opening positions for two discourse arguments. Discourse connectives
include coordinating conjunctions (e.g. and, but), subordinating conjunctions (because, if ) and

3. Basically a constituency tree, which is in its nature projective and does not allow crossing edges, in comparison to
the basic mathematical definition of a tree graph.

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DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

discourse adverbials (nevertheless). Apart from connectives, the two discourse arguments of a dis-
course relation (and their extent) and the semantic type (sense) of a discourse annotation were anno-
tated. In 2004, the first version of Penn Discourse Treebank was released (Miltsakaki et al., 2004).
The second release of the PDTB four years later includes annotation of the ca. 49,000 sentences of
the Wall Street Journal part of the Penn Treebank (Prasad et al., 2008). Apart from explicit connec-
tives, other phenomena have been annotated in this version, mainly implicit relations and attribution
(attributing beliefs and assertions to agents making them) alternative lexicalization of a connective
(AltLex, e. g. that is why), entity based relations (EntRel) and places with weak coherence (NoRel).
In its latest version PDTB 3.0 (Prasad et al., 2018, Prasad et al., 2019), the annotations were en-
riched by many relations mostly in intra-sentential contexts, the sense taxonomy was revised and
the existing annotations enhanced in many aspects.

The PDTB-style connective/argument analysis has become very popular, also because such an
analysis requires less interpretation and pragmatic inference than the RST analysis. The PDTB
authors also claim that their approach is theory-neutral, independent from any syntactic theory, and
as such can be transferred to other languages.

In the first part of our analysis on configurations of positionally close relation pairs (4.1), we re-
late our findings to a similar research conducted on the second version of the English Penn Discourse
Treebank in Lee et al. (2006). The aim of their study was to describe and quantify the configurations
of discourse relations as typical or less typical in terms of discourse complexity. The complexity
of discourse configurations there is being compared to the complexity of relations in syntax, but
also refers to the principles of the global Rhetorical Structure Theory, in particular the representa-
tion of any text document as a single tree-like structure with strong constraints. The study actually
tries to answer the question whether their empirical locally annotated data would fulfill or violate
these strong constraints. Therefore Lee et al. (2006) studied various types of overlaps of discourse
relations. They encountered a variety of patterns between pairs of discourse relations, including
nested (hierarchical), crossed and other non-tree-like configurations. Nevertheless, they conclude
that the types of discourse dependencies are highly restricted since the more complex cases like
crossings and partial overlaps can be factored out by appealing to discourse notions like anaphora
(non-structural, possibly long-distance tie) and attribution (attribution span as a known mismatch
between the syntactic and discourse structure), and argue that pure crossing dependencies, partially
overlapping arguments and a subset of structures containing a properly contained argument should
not be considered part of the discourse structure. The authors challenge Czech discourse researchers
to introduce a similar study (footnote 1 in their paper, ibid.) in order to observe and compare the
complexity of discourse and syntax dependencies in two typologically different languages.4

3. Data and Tools

Our study is based primarily on two data resources: for Czech, the Prague Discourse Treebank 2.0
(PDiT; Rysová et al., 2016, Zikánová et al., 2015),5 and, for English, the Penn Discourse Tree-

4. From this viewpoint, we do not assume substantial differences between the two languages in discourse structure
itself. However, there are surely larger differences on “lower” levels of linguistic description, in our case most
visibly connective repertoires and syntactic properties of the two languages, which can in the outcome influence
some motivations in the annotation design and thus effect the resulting discourse structure, compare Mírovský et al.
(in prep.).

5. Please note that the discourse annotation in PDiT 2.0 is the same as in PDT 3.5 (Hajič et al., 2018) and the upcoming
PDT-C 1.0, which are newer versions of the PDiT 2.0 data.

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POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

CONTRAST EXPANSION

confrontation conjunction
opposition conjunctive alternative
restrictive opposition disjunctive alternative
pragmatic contrast instantiation
concession specification
correction equivalence
gradation generalization

CONTINGENCY TEMPORAL

reason–result synchrony
pragmatic reason–result precedence–succession
explication
condition
pragmatic condition
purpose

Table 1: Semantic types of discourse relations in the PDiT 2.0

bank ver. 3.0 (PDTB; Prasad et al., 2019). These two corpora are comparable in size (approx. 50
thousand sentences each), genre (journalistic texts) and they have both been manually annotated for
discourse relations in comparable approaches (PDTB and the PDTB-like modification in the PDiT).
Namely, for explicit relations, all connectives in a given text were identified, their two arguments
were detected and a semantic/pragmatic relation6 between them was assigned to the relation. Dis-
course connectives in PDiT 2.0 are of two types: primary and secondary, according to Rysová and
Rysová (2014). Primary connectives are defined as grammaticalized expressions such as because
or therefore whereas secondary connectives are not (yet) fully grammaticalized structures such as
except for this, the reason was or for this reason. The notion of secondary connectives in Prague
Treebank roughly corresponds to the categories of AltLex and AltlexC (alternative lexicalization
tokens and alternative lexicalization constructions) in PDTB 3.

The PDTB and PDiT use similar sets of discourse relation types – the set of discourse types in
PDiT is inspired by the Penn Discourse Treebank 2.0 sense hierarchy (Prasad et al., 2008), see the
complete list in Table 1. The taxonomy is two-level, but in the annotation only the second-level
relations can be assigned. Confrontation in the Czech taxonomy equals to the original juxtaposition
in the PDTB 2 (mostly represented by connectives like while, whereas), restrictive opposition also
includes exception (only, except that...), correction equals to substitution (not A, but B, instead),
explication is giving evidence by other means than reason-result.7 Pragmatic labels are used in
accordance with the PDTB 2 pragmatic labels.

6. "sense" in the PDTB terminology, "discourse type" in PDiT 2.0
7. strongly represented by a typical Czech connective totiž (actually, since, I mean, as a matter of fact)

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DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

PDiT 2.0 contains 21 223 explicit discourse relations (i.e. relations signalled by explicit dis-
course connectives, both primary and secondary),8 while the PDTB 3 contains 25 696 such relations
(we take into account relations of type Explicit, (AltLex) and AltLexC).9

Both PDiT and the PDTB are available in the Prague Markup Language format (PML; Pa-
jas and Štěpánek, 2008),10 an XML-based format and application framework designed for multi-
layer linguistic annotations with available tools allowing for complex linguistic studies over PML
data: btred for scripting in Perl and Prague Markup Language - Tree Query (PML-TQ; Pajas and
Štěpánek, 2009) as a graphically oriented querying system.

4. Analysis

This section is divided into four subsections according to the research directions in which we ad-
dress different aspects of a higher/global text structure traceable in locally annotated corpora. 4.1 –
configurations of pairs of discourse relations, a study carried out on the basis of a similar research
by the PDTB group and, like this study, contributing to the debate on acceptable “shapes” of an
interconnected coherence representation of a text; 4.2 – hierarchies of nested discourse relations –
a study that reveals if local discourse relations, without having the underlying assumption of hierar-
chy, also exhibit some type of hierarchical structure; 4.3 – paragraph-initial senses and connectives,
a survey on cross-paragraph coherence in comparison to intra-paragraph settings; and 4.4 – rela-
tions with large arguments, as these are rather unexpected/unusual in local settings and can denote
possible non-elementary units of higher text structuring.11

4.1 Configurations of Close Relation Pairs

For this part of the analysis, and also for the subsequent one described in 4.2, we take advantage
of the fact that the corpora used in the PDTB and our studies are comparable in many aspects (as
mentioned earlier) and also contain a similar number of annotated discourse relations (approx. 20
thousand). However, it is important to notice that Lee et al. (2006) included also implicit relations
in their study and conducted the research on the older version of the PDTB (2.0). The Lee et al.
(2006) study defines six basic types of patterns of relation pairs: independent relations, full embed-
dings, shared arguments, properly contained arguments, pure crossings and partially overlapping
arguments. In our analysis, we decided to make a more fine-grained classification of the patterns
to cover all possible settings and to get more detailed insight into the configurations, and ended up
with 17 categories, compare Table 2. Sometimes we also use different pattern naming (e.g. inde-
pendent relations vs. adjacency), but for those patterns accounted for in both studies, we state how
the names map.

In our data, we have collected and classified types of relative positions of neighbouring discourse
relations in the corpus, using a scripting tool btred as a part of an application framework for PDiT-

8. We exclude the 361 list relations from this study, i.e. relations between subsequent members of enumerative struc-
tures. They represent a special text structure on their own, and as such, in the Prague approach they stand aside the
binary discourse relations and discourse type taxonomy.

9. Implicit discourse relations have been annotated on a part of the PDiT 2.0, see Zikánová et al. (2019); this annotation
was not taken into account in the present analysis, as the size of the implicit datasets is different at present.

10. The PML is the primary publication format for PDiT. The English PDTB was first transformed to the PML format,
for the purposes of studying discourse annotations in a unified format.

11. The first and the second subsections/topics are closely related, as hierarchies are a subset of possible relation config-
urations (nested relations pattern), but we keep them separate in the study.

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POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

Line Frequency in PDiT Pattern Visualization

1 6 572 (983) adjacency <---------> <--------->
37.3% (32.9%) <=========> <=========>

2 1 923 (865) progress <---------> <--------->
10.9% (29.0%) (shared argument) <=========> <=========>

3 51 (21) total overlap <---------> <--------->
0.3% (0.7%) <=========> <=========>

4 266 (116) left overlap <---------> <--------->
1.5% (3.9%) right adjacency <=========> <=========>

5 25 (10) left overlap <---------> <--------->
0.1% (0.3%) right contained <=========> <===>

6 31 (10) right overlap <---------> <--------->
0.2% (0.3%) left adjacency <=========> <=========>

7 17 (8) right overlap <---------> <--------->
0.1% (0.3%) left contained <===> <=========>

8 250 (146) containment I <---------> <--------->
1.4% (4.9%) <===> <=========>

9 190 (150) containment II <---------> <--->
1.1% (5.0%) (opposite) <=========> <=========>

10 83 (14) both args <---------> <--------->
0.5% (0.5%) contained I <===> <===>

11 73 (8) both args <---------> <--->
0.4% (0.3%) contained II <===> <=========>

12 3 591 (299) left hierarchy <---------> <--------->
20.4% (10.0%) <===> <===>

13 3 543 (56) right hierarchy <---------> <--------->
20.1% (1.9%) <===> <===>

14 10 (10) crossing <---------> <--------->
0.1% (0.3%) <=========> <=========>

15 883 (196) envelopment <---------> <--------->
5.0% (6.6%) <=========> <=========>

16 3 (2) partial overlap <---------> <--------->
0.0% (0.1%) <=========> <=========>

17 8 (5) partial overlap II <---------> <--------->
0.0% (0.2%) <===============> <=========>

Table 2: Patterns of adjacent, overlapping or embedded pairs of explicit discourse relations in
PDiT 2.0. The column visualization shows relative position of the arguments read from
left to right; arguments of one relation are marked with ’-’, the other one with ’=’. The
total number of such close relations in PDiT was 17 628; 109 of them (0.6%) did not fit
the listed patterns. Numbers in brackets mean frequencies if only inter-sentential discourse
relations (arguments in different sentences) were taken into account; in total, there were
2 984 such close relations in PDiT, 85 of them (2.8%) did not fit the listed patterns.

types of corpora (Pajas and Štěpánek, 2008). We define a close relation pair as a pair of discourse
relations that are either adjacent (the left argument of one relation immediately follows the right

10


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

argument of the other relation), or they overlap in one of many possible patterns. We first analyze
the detected patterns in PDiT and, next, a specific subsection is devoted to the description of the
detected hierarchical structures (4.2).

We were able to detect 17 628 close relation pairs in PDiT, and for each such pair, we inves-
tigated its pattern, the mutual arrangement of the two relations. In Table 2, these patterns are also
graphically illustrated. The table shows figures for all explicit relation pairs and, in brackets, for
inter-sentential relation pairs only.

The most common settings for close relations in PDiT are pure adjacency (succession) of two
relations (line 1: 6 572 cases in PDiT), and “full embeddings”, in other words two-level hierarchies,
in total 7 134 in PDiT (lines 12 and 13). These configurations (lines 1, 12 and 13) represent together
slightly more than 3/4 of all detected patterns in PDiT. They are also referred to as very “normal”
structural relationships in Lee et al. (2006, p. 82).

The next-largest group is progress (line 2), a shared argument in the PDTB terminology, with
1 923 instances or 10.9% of all patterns. Lee et. al. report 7.5% of this type, which is fairly
comparable.

Total overlap (line 3) is caused by the possibility to annotate two different relations between
the same segments for co-occurring connectives, as in because for example or but later. It occurs
51 times (0.3%) in PDiT. This pattern may vary a lot in different annotation schemes, as there
may be different approaches to handling co-occurring connectives, or even the possibility of a a
co-occurrence of an explicit and an implicit relations between the same segments, which is the
approach taken by some newer corpora, e.g. by the PDTB in its version 3.

The envelopment (line 15) concerns in the vast majority of cases a non-adjacent (long-distance)
relation and another relation placed in the text between the arguments of the non-adjacent rela-
tion. The enveloped relation is often a sentence with an inner syntactic structure annotated. The
same is often true for hierarchical patterns (lines 12 and 13) and it explains the big difference ob-
served in both corpora between all detected envelopment and hierarchical patterns and only the
inter-sentential ones. Linguistically, some of the envelopment cases are sentences headed by two at-
tribution spans (verbs of saying) and some structure in the reported content in between, also cases of
two linked reporter’s questions in an interview and the inner structuring of the interviewee’s answer,
but also texts with no striking structural reasons for such an arrangement. In PDiT, envelopment
represents ca. 5% of all settings and is certainly worth of further investigation.

Patterns with properly contained arguments, either one of the arguments (lines 5, 7, 8 and 9)
or both (10 and 11), very often involve “skipping one level” in the syntactic tree of a sentence, see
Example 212 of the type 8 (containment I), i.e. exclusion of a governing clause from the argument
(mostly an attribution span), that makes its syntactically dependent clause (mostly a “reported-
content-argument”) to a subset of an other argument of the other relation represented (mostly) by a
whole sentence. In Example 2, the text span a young researcher works with enthusiasm for science,
regardless of salary is a left-sided argument of the but-relation (in bold) and, at the same time a
subset, properly contained, in a larger right-sided argument of the therefore-relation (in italics).
The governing clause It is therefore appropriate... the fact that is thus the mismatch, it represents
the difference between proper containment and the much more frequent shared argument pattern
(line 2).

12. From now on in the annotated examples, relation 1 is highlighted in italics, relation 2 in bold. The connectives are
underlined.

11


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

(2) The gap in the standard of living that appears between the qualified scientific elite and the
business sphere, right now, at the beginning of the transformation of the society, will leave
traces. It is therefore appropriate to pamper young researchers and not misuse the fact that
a young researcher works with enthusiasm for science, regardless of salary. But a person
who begins to find his mission in research also starts a family, wants to live at a good
place and live with dignity.
Czech original: Mezera na úrovni životního standardu, která se objevuje mezi kvalifikovanou vědeckou
špičkou a sférou podnikatelskou, právě ted’, v počátcích transformace společnosti, přece jen zanechá
stopy. Je tedy namístě hýčkat dorost a nehřešit na to, že mladý badatel pracuje s nadšením pro vědu,
bez ohledu na plat. Jenže člověk, který začíná nalézat své poslání ve výzkumné práci, také za-
kládá rodinu, chce bydlet a důstojně žít.

Besides the discussed attribution (introductory statements) that has been excluded from the argu-
ment, this mismatch in the shared argument extent is also the case of the annotation of some sec-
ondary connectives realized by whole clauses (like This means that..., Example 3, type 9, contain-
ment II). These verb phrases are not treated as parts of any of the arguments they relate to and pose
a methodological issue. In the representation in Example 3, the clause This means that is not in
italics, it is not considered to be a part of any argument of the left relation, i. e. the relation it
anchors.

(3) This brief overview essentially exhausts the areas of notarial activities within the framework
of free competition between notaries. This means that in these notarial agendas, the client
has the option of unlimited choice of notary at his own discretion, as the notary is not
bound to the place of his work when providing these services.
CZ: Tímto stručným přehledem jsou v podstatě vyčerpány oblasti notářských činností v rámci volné
konkurence mezi notáři. To znamená, že v těchto notářských agendách má klient možnost neome-
zeného výběru notáře podle vlastní úvahy, nebot’ notář při poskytování těchto služeb není vázán
na místo svého působení.

A third setting concerns multi-sentence arguments, where the contained argument is typically a
single sentence. Patterns with properly contained arguments (lines 5, 7 – 11) represent in total 3.6%
(638) of all patterns in PDiT.

A (pure) crossing is a setting where the left-sided argument of the right relation comes in be-
tween the two arguments of the left relation, compare line 14 in Table 2. Pure crossings violate
the RST constraints most visibly, with crossing edges, so the debate on tree adequacy often cir-
cles around the acceptability of crossings in discourse analysis. Lee et al. (2006) identify 24 cases
(0.12%) of crossings in the PDTB2. We detected only 10 such cases in PDiT, which is a very
small proportion. Manual inspection of the cases of crossing revealed several different scenarios,
from clearly incorrect annotation, more interpretations possible, across cases with attribution spans
in between, to a few, in our opinion, perfectly sound analyses, as exemplified by Example 4 from
PDiT.

(4) (a) What can owners and tenants expect, what should they prepare for?
(b) The new legislation should allow all owners to sell apartments. (c) It is most urgent
for flats owned by municipalities, as they manage about a quarter of the housing stock
of the Czech Republic and some are - mainly for financial reasons - interested in mon-

12


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

etizing a part of their apartments. (d) The law should also allow to complete transfers of
housing association apartments and their sale to its members. (e) This is also not a “small
portion”, but a fifth of the total number of dwellings.13

CZ: (a) S čím mohou vlastníci i nájemci počítat, na co by se měli připravit?
(b) Nová právní úprava by měla umožnit všem vlastníkům prodávat byty. (c) Nejnaléhavěji to vys-
tupuje do popředí u bytů ve vlastnictví obcí, protože ty spravují asi čtvrtinu bytového fondu
České republiky a některé mají - především z finančních důvodů - zájem část svých bytů
zpeněžit. (d) Zákon by měl také umožnit dokončení převodu i možnost prodeje družstevních bytů
členům. (e) Ani zde nejde o “malou porci”, ale o pětinu celkového počtu bytů.

If we accepted the possibility that not only (b), but a larger (b+c) unit relates to (d) in the also-
relation, which would be a completely fine interpretation in the Prague annotation, the relation of
(e) – the neither-relation – in our view still cannot accept just (d) as its left-sided argument. We
also think this case cannot be factored out due to anaphora. There is, for sure, room for different
interpretations within different theories, we just offer our data, state our view and admit that crossing
structures are extremely rare even in our empirical data.

Partial overlap is a type of structure that violates the RST tree constraint, too. Lee et al. (2006)
could only find 4 such cases. We detected 11 cases in PDiT (lines 16 and 17 of Table 2). They often
include large arguments of untypical range (2.5 sentences etc.) which can be questioned. Some of
the relations also include secondary connectives with strong anaphoric links (in this respect, given
the fact that etc.). These relations can be factored out, yet, again, even among the small number of
cases in PDiT there were linguistically acceptable ones, compare Example 5 (partial overlap II).

(5) The responsibility of the future tenant of this 103,000-square-metre area will be to care for
all properties, including their maintenance and repairs. The tenant will also have to resolve
the parking conditions for market visitors and to meet the conditions of the Prague Her-
itage Institute during construction changes due to the fact that the complex is a cultural
monument. The capital city at the same time envisages preserving the character of the
Holešovice market.
CZ: Povinností budoucího nájemce tohoto areálu o rozloze 103 tisíc metrů čtverečních bude mj.
péče o všechny nemovitosti včetně jejich údržby a oprav. Nájemce bude také muset vyřešit pod-
mínky parkování pro návštěvníky tržnice a splnit podmínky Pražského ústavu památkové péče při
úpravách objektů vzhledem k tomu, že jde o kulturní památku. Hlavní město přitom počítá se
zachováním charakteru holešovické tržnice.

4.2 Hierarchies

The purpose of looking for hierarchical structures in the locally annotated data is to discover to
what extent such an annotation shows signs of some higher (global) structure, too. We do not
claim that the trees detected by us are the trees a global analysis like RST would discover, but we
demonstrate the existence of some hierarchical text structure in local annotation. Some of it could
perhaps partially match to RST-formed subtrees (and definitely there would be an intersection of
separate relations, compare e.g. intersections in Wall Street Journal local and global annotations in

13. The “also-not” connective is originally in Czech ani, in the meaning of neither. Lit. translation: “Neither here
is_concerned a small portion...”

13


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

Line Frequency Depth Hierarchy

1 381 (10) 3 A ( B ( C ))
2 64 (1) 3 A ( B ( C ) D )
3 50 3 A ( B C ( D ))
4 23 (1) 3 A ( B ( C ) D ( E ))
5 20 3 A ( B ( C D ))
6 0 (1) 3 A ( B ( C ) D E )
7 0 (1) 3 A ( B C ( D ) E )
8 19 4 A ( B ( C ( D )))
9 7 4 A ( B ( C ( D )) E )

10 5 4 A ( B C ( D ( E )))
11 5 4 A ( B ( C ( D )) E ( F ( G )))

...
12 2 5 A ( B ( C ( D ( E ))) F )
13 1 5 A ( B C ( D ( E ( F ))) G )
14 1 5 A ( B ( C ( D ) E ( F ( G ))) H I J ( K ))
15 1 5 A ( B ( C ( D ( E ))))
16 1 5 A ( B ( C ( D E ( F ))))

Table 3: Selected schemes of hierarchies of explicit discourse relations in PDiT. Numbers in brack-
ets mean frequencies of hierarchy schemes if only inter-sentential discourse relations were
taken into account (no other inter-sentential hierarchies were encountered in the data).
The three dots in the middle of the table indicate that there can be more cases of different
4-level hierarchy patterns.

Poláková et al., 2017), but this is yet to be investigated. We are also aware, as pointed out in Egg
and Redeker (2010), that minimal, local annotations do not normally form a connected graph.14

4.2.1 HIERARCHIES IN THE PDIT 2.0

For the study of hierarchical structures, we used pairs of nested relations where one of the relations
is as a whole included in one argument of the other relation (patterns corresponding to lines 12 and
13 from Table 2) to recursively construct tree structures out of pairs of the nested relations. Based
on the quantitative results, we inspected selected samples of the detected patterns manually, in order
to check the script outcome and to provide a linguistic description and comparison. The results on
the whole PDiT data are displayed in Table 3, arranged according to the scheme of such hierarchy
trees (identical structures are summed and represented by the hierarchy scheme). We only mention
cases where there are at least three levels in the tree, as two-level hierarchies are part of Table 2.

For explanation: The scheme “A ( B )” means that the whole relation B is included in one of the
arguments of the relation A (this is, of course, only a two-level tree). The scheme “A ( B C ( D ))”

14. And the more so, as we do not include implicit and entity-based relations into our study.

14


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

means that relations B and C are all included in the individual arguments of relation A (without
specifying in which argument they are, so they can be both in one argument or each in a different
argument) and the relation D is completely included in one of the arguments of relation C. It is
a three-level hierarchy. Generally, we count the depth (number of levels) of a hierarchy tree as a
number of nodes in the longest path from the root to a leaf.

There are many sub-hierarchies in a large/deep hierarchy, for example “B ( C ( D ))” is a sub-
hierarchy of “A ( B ( C ( D )) E )”; such sub-hierarchies, however, are not counted in Table 3, i.e.,
each hierarchy is only counted in the table in its largest and deepest form as it appeared in the PDiT
2.0 data.15

In the PDiT data, local discourse relations form hierarchies up to five levels. We have identified
5 patterns of 5-level hierarchies (5-LH), with the total of 6 instances, see Table 3. There is also a
number of 3- and 4-level hierarchies. An analysis of random samples (and of all the deepest ones)
revealed, surprisingly, that there may be a 4-level hierarchy spanning 11 sentences, but also a 5-LH
spanning only two sentences, from which one is typically a more complex compound sentence. The
“longest” of the 5-LHs includes also 11 sentences (line 14) and it also exhibits branching (D, G and
K as leaves, where the G-path is the deepest). One of the 5-LHs should be in fact one level flatter
(line 12), as the lowest two relations are three coordinated clauses with two and-connectives: “the
troops protected them and fed them and gave them the impression that they were invulnerable...”.
Such structures are notoriously hard to interpret for any framework, yet in Prague annotation, the
annotation is incorrectly hierarchical where it should have been flat.

For a better illustration of the hierarchical configuration of the relations, a text sample with a 4-
LH is analyzed in Appendix 1 to this study. It covers one whole paragraph and a part of a preceding
one (11 sentences). Its pattern is A ( B ( C ( D ) E ) F G ).16

To find out how much structure is involved only within individual sentences, i.e. how much
of sentential syntax forms the hierarchies, in a second phase we filtered out all intra-sentential
relations. The numbers in brackets give counts for patterns of hierarchies, if only inter-sentential
relations (i.e. arguments in different sentences) are accounted for.17 The hierarchies of this type
are much less frequent and their maximum depth is just 3, which implies that beyond the sentence
boundary, local annotation of explicit connectives does not represent hierarchical text structuring
very often in the PDiT 2.0.

4.2.2 HIERARCHIES IN THE PENN DISCOURSE TREEBANK 3.0

Having at our disposal the Penn Discourse Treebank 3.0 annotations converted into the Prague PML
format (Poláková et al., 2017), we can use the same procedure to search for hierarchical structures
also in these English locally annotated data. We take into account relations of the type Explicit,
AltLex and AltLexC. The results are summed up in Table 4. Similarly as in the experiment with the
Czech data, we have detected hierarchies of relations up to 5 depth levels. Overall, their counts are

15. This also explains the zeros in Table 3. The empty line in the table suggests that there are more different patterns of
hierarchies of the given depth, the same holds also for Table 4.

16. We do not present a 5-LH here, as the largest one is too complex and the smaller ones include two sentences only, so
the main structure is syntactic in nature.

17. Please note that hierarchies counted in brackets (without intra-sentential relations, column 3 in Tables 3 and 4) are
not a subset of the respective hierarchies from the same table row that also include intra-sentential relations – adding
intra-sentential relations into the hierarchies means that a particular hierarchy pattern may change (be enlarged). This
happens most clearly in lines 6 and 7 of Table 3.

15


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

Line Frequency Depth Hierarchy

1 232 (2) 3 A ( B ( C ))
2 63 (2) 3 A ( B ( C ) D )
3 46 (2) 3 A ( B C ( D ))
4 20 3 A ( B ( C D ))
5 10 3 A ( B ( C ) D ( E ))
6 8 3 A ( B ( C ) D E )

. . .
7 2 (1) 3 A ( B ( C ) D E F )

. . .
8 5 4 A ( B ( C ( D )) E )
9 3 4 A ( B ( C ( D )))

10 2 4 A ( B ( C ( D ) E ) F )
11 1 4 A ( B C D E F ( G ( H )))
12 1 4 A ( B ( C D ( E ) F ) G ( H ) I ( J ) K ( L ))

. . .
13 1 5 A ( B C D ( E ( F ( G ))))

Table 4: Selected schemes of hierarchies of explicit discourse relations in the PDTB 3.0. Numbers
in brackets mean frequencies of hierarchy schemes if only inter-sentential discourse re-
lations were taken into account (no other inter-sentential at least 3-level hierarchies were
encountered in the data).

slightly lower, e.g. the simplest 3-LH pattern (A (B (C)) is 232 in comparison to 381 in the Czech
data. The maximum depth is also 5 but there is only one such detected hierarchy, compare the last
line of Table 4. The source text with all the relations annotated within this hierarchy is presented in
detail in the Appendix 2 to this study. The hierarchy spans across 2 paragraphs (7 sentences), and
its pattern is A ( B C D ( E ( F ( G )))), which implies that the relations B and C do not take part
in the deepest branch of the hierarchy, they are only included in the highest relation A. Further, it
can be observed that the two lowest relations, G (the deepest one) and F, are intra-sentential, while
the hierarchy crosses the sentence boundary with its relation E, which is the lowest inter-sentential
relation. So, only the relations A and D, the arguments of which span across two or more sentences18

in our understanding contribute in a way to a higher discourse structure.
The number of hierarchies formed by inter-sentential relations only is even lower in the PDTB 3,

only 7 (compared to 14 in the PDiT 2.0), with the same maximum depth of 3 levels. A hypothesis
for the relatively small number of hierarchies built by only inter-sentential relations in both corpora
is that only some of the connectives operating at higher discourse levels were identified and anno-
tated as such, some of them were assigned local coherence links due to the minimality principle.19

18. more precisely, one argument in each of them spans two or more sentences
19. The minimality principle instructs the annotators to mark as an argument as many clauses and/or sentences as are

minimally required and sufficient for the interpretation of the relation. It was applied both in PDTB and in PDiT

16


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

Number of documents 3 165
Number of sentences 49 431
Number of sentences without headings, captions and metatext 44 979
Number of paragraphs 14 790
Number of paragraphs without headings etc. 11 643
The average number of sentences per paragraph21 3.9

Table 5: Basic properties of the inner structure of texts in the Prague Discourse Treebank

This issue was recently discussed in Poláková and Mírovský (2019) with focus on paragraph-initial
connectives and we dedicate the following subsection to this topic.

4.3 Paragraph-initial Semantic Types and Connectives

A possible different scope of connectives in paragraph-initial positions was previously indicated
in a study analyzing discourse connectives with anaphoric properties and their ability to relate to
a distant, non-adjacent left-sided argument (Poláková and Mírovský, 2019). A special set of cases
was defined where the connective actually does not relate to a short non-adjacent segment on its left,
but to an adjacent, quite larger segment of text and is interpretable as a means of higher discourse
structuring. From another perspective on paragraph boundary, cross-paragraph discourse relations
were recently investigated in Prasad et al. (2017) for implicit relations, leading to the observation
that a first sentence in a given paragraph semantically relates to the immediately preceding last
sentence of the previous paragraph in only 52% of their sample, with 48% having links to non-
adjacent left contexts.

Our analysis of the features of cross-paragraph coherence only takes explicit relations into ac-
count (including secondary connectives), although we acknowledge that implicit connecting or other
signalling is common between paragraphs. We focus on the following issues: (i) Is there a differ-
ence between the semantics of discourse relations that ensure continuity between paragraphs on one
side, and relations within an individual paragraph on the other? Are certain relations more typical
for cross-paragraph coherence, while others are typically local? (ii) Are discourse connectives in
the cross-paragraph usage different from locally used connectives?

Because of limitations of the actual version of the conversion of the PDTB data to the PML
format, in this subsection and also in the study of paragraph-initial connectives in the subsequent
subsection we only examined texts of the Prague Discourse Treebank 2.0 (as characterized in Ta-
ble 5), via PML-TQ queries and using information about paragraph numbers available at roots of
the deep-syntactic trees.20

In terms of the higher structure and local relations in a text, three sets of relations can be dis-
tinguished. First of them are the relations between paragraphs, or cross-paragraph relations, as the
top set (1). The rest, i.e. intra-paragraph relations, can be divided into inter-sentential (2) and intra-

annotations. The PDTB moreover annotates supplementary material to an argument, where needed (Prasad et al.,
2008).

20. Information about paragraph numbers in a direct form of attribute para_no is only available in the PDiT data accessi-
ble via the PML-TQ search engine and is taken from identifiers (attribute id) of t-roots – roots of the tectogrammatical
trees.

21. The average length of a paragraph is counted after the exclusion of headings, captions and metatext, i.e.
44 979 / 11 643.

17


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

(1) Cross-par inter-S (2) Intra-par inter-S (3) Intra-S

conjunction 236 opposition 1 584 conjunction 6 154
opposition 207 conjunction 1 322 reason-result 1 663
reason-result 125 reason-result 1 056 condition 1 400
confrontation 44 confrontation 273 opposition 1 388
generalization 43 concession 252 concession 633
specification 42 precedence 240 precedence 592
concession 32 gradation 197 specification 521
instantiation 22 explication 155 purpose 412
precedence 20 restr. opposition 153 confrontation 348
restr. opposition 19 correction 127 correction 323

Table 6: 10 most common semantic types of explicit discourse relations for each dataset (number
of occurrences)

sentential ones (3); the differences between these groups are mainly due to the syntactic structure. In
our analysis, we want to focus specifically on the relations between paragraphs (1). These relations
do not reflect syntactic structure that much, which is why we compare them mainly to the sepa-
rate group of intra-paragraph inter-sentential relations (2). However, in order to keep the picture of
discourse relations complete, we also include a comparison with (intra-paragraph) intra-sentential
relations (3).

Thus, we focused on three datasets. For the cross-paragraph relations (dataset 1), we analyzed
explicit discourse relations which connect the first sentence of the paragraph to any previous text.
As for local relations (2), the set in question concerns explicit inter-sentential discourse relations
that do not go beyond the scope of one paragraph. The relations in the set (3) connect arguments
within one syntactic tree (sentence), i.e. they cross neither the sentence boundary, nor the paragraph
boundary.22

The distribution of semantic types of discourse relations across all the datasets differs signifi-
cantly, see Table 6 and the graph in Figure 2, the significance was verified using the χ2 test.

The vast majority of instances (63-68 percentage points in all three datasets) belong to three
discourse relations, namely conjunction, opposition, and reason-result. In cross-paragraph rela-
tions, conjunction comes first, whereas in intra-paragraph inter-sentential relations, opposition is
most common. Within intra-sentential relations, conjunction absolutely predominates with 42% of
occurrences, and the very frequent relation of condition comes as third, compare details below.

In the top ten of the cross-paragraph relations, some relations typically occur which are not in
the top ten of the intra-paragraph relations, namely specification, generalization, and instantiation.
Often, the following paragraphs in our data expand the content of the previous text in this way.
On the other hand, we cannot consider the relation of specification as only typical in the higher

22. Theoretically, there could be cross-paragraph intra-sentential discourse relations, too, such as lists of dependent
clauses printed each in a different paragraph, cf.

The request will be accepted
- if the applicant comes from the EU, and
- if he/she encloses two letters of recommendation.
We do not deal with such sentences in this paper since their occurrence is marginal.

18


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Cross-par inter-S
Intra-par inter-S
Intra-S

Figure 2: A graph for Table 6 showing percentages of the semantic types for the three datasets,
i.e. for cross-paragraph (first column), intra-paragraph inter-sentential (second column),
and intra-sentential discourse relations (third column). In each dataset, all its occurrences
sum to 100%.

text structure, since it also occurs in the top 10 intra-sentential relations. We can assume that some
structural features of specification in the datasets (1) and (3) differ; these features will be an object
to a further research. In the top ten of the intra-paragraph inter-sentential relations (dataset 2), on the
other hand, gradation, explication and correction are present, representing probably another way of
text progression typical for smaller units.

The datasets (1-3) differ not only in proportions of frequent semantic types, but also in those
which are the least represented in the respective datasets. We have looked into semantic types of
discourse relations which are represented by less than 1% of occurrences in each of the analyzed
datasets, see Table 7.

As can be seen from Table 7, some relations are rare in our data in general, independently
from paragraph boundaries and syntactic structure. This is the case of all the pragmatic relations,
equivalence and conjunctive alternative. Another group of relations has a low representation in the
dataset (1) and (2), but they are quite typical for intra-sentential relations (dataset 3). This applies
to condition and purpose, see Table 6 and Table 7. We can consider these relations as typically
syntactic and local. The relation of correction is usually not used across paragraphs. However, it
is typical for both types of intra-paragraph relations. Finally, we can find typical relations of the
higher structure in our data (dataset 1), too, which occur in the intra-sentential structure (dataset 3),
namely instantiation and generalization.

Let us sum up the observations concerning semantics of discourse relations in the datasets (1-3).
Distributions of semantic types in inter-sentential relations (datasets 1 and 2) are quite close to each
other, but they differ from intra-sentential relations distinctly. This finding was confirmed by the
result of χ2 tests, too. In other words, inter/intra-sententiality is a more important feature for the
semantics of discourse relations than the presence or absence of paragraph boundary. Nevertheless,

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POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

(1) Cross-par inter-S (2) Intra-par inter-S (3) Intra-S

equivalence 8 equivalence 57 explication 115
synchrony 3 synchrony 49 restr. opposition 99
correction 3 condition 42 conj. alternative 70
pragm. reason-result 2 pragm. contrast 27 equivalence 42
condition 1 pragm. reason-result 27 instantiation 27
disj. alternative 1 conj. alternative 20 pragm. contrast 23
conj. alternative 0 disj. alternative 14 pragm. reason-result 16
purpose 0 purpose 7 pragm. condition 16
pragm. contrast 0 pragm. condition 1 generalization 12
pragm. condition 0

Table 7: Distribution of semantic types with occurrence <1% for each dataset (number of occur-
rences)

cross-paragraph relations (dataset 1) have specific features distinguishing them from intra-paragraph
relations (datasets 2 and 3), too. Besides the most frequent relations the distributions of which are
very similar for all the three datasets (conjunction, opposition, reason-result), cross-paragraph rela-
tions typically express different meanings of expansion (generalization, specification, instantiation).
On the other hand, they rarely express semantics of correction which is typical for intra-paragraph
relations (datasets 2 and 3); moreover, some typical intra-sentential relations, such as condition,
purpose, disjunctive alternative and synchrony almost do not occur across paragraphs in our data.

4.3.1 DISCOURSE CONNECTIVES IN PARAGRAPH-INITIAL POSITIONS

We also addressed the question of the differences in the use of discourse connectives across para-
graphs and in local relations. We focused on the three most common relations, conjunction, oppo-
sition and reason-result, and the connectives by which these relations are expressed (see Table 8).
The analysis showed that the relation of conjunction is often expressed by specific discourse connec-
tives in the cross-paragraph context, namely with the adverb dále [further, next] and the particle také
[too, also]. The basic and most frequent discourse connective for conjunction a [and] is much more
frequently used in the datasets (2) and (3), i.e. in the intra-paragraph structure. Further, in the intra-
paragraph coherence, discourse connectives based etymologically on a prepositional phrase with an
anaphoric element are common, cf. přitom [at the same time, lit. by that], and its intra-sentential
relative variant přičemž [and/while, lit. by which]. Discourse connectives based on relatives are not
used in the inter-sentential structures.

Discourse connectives for opposition are almost identical for cross-paragraph and intra-paragraph
inter-sentential relations (dataset 1 and 2). A typical discourse connective in both these groups is
však [however], whereas intra-sententially (dataset 3), opposition is predominantly expressed by
the conjunction ale [but]. In dataset (3), multi-part discourse connectives are used (with an non-
autonomous part sice [sure/true]) which are not used inter-sententially.

Similarly, discourse connectives used for reason-result are very close in the datasets (1) and
(2). Again, a specific set of discourse connectives is used in the intra-sentential context (dataset 3).
Moreover, these two larger groups (inter-sentential datasets 1 and 2, and the intra-sentential set 3)

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DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

(1) Cross-par inter-S (2) Intra-par inter-S (3) Intra-S

5 most common discourse connectives: conjunction

dále [further] 42 a [and] 309 a [and] 5 364
také [too] 32 také [too] 193 což [which] 165
a [and] 28 dodal [he added] 78 přičemž [by which] 71
rovněž [also] 25 rovněž [also] 74 a také [and also] 45
dodal [he added] 11 přitom [at the same time] 73 podobně [similarly] 39

5 most common discourse connectives: opposition

však [however] 123 však [however] 906 ale [but] 732
ale [but] 33 ale [but] 310 však [however] 221
ovšem [yet] 24 ovšem [yet] 154 sice - ale [true/sure - but] 143
avšak [however] 4 jenže [but/only] 39 ovšem [yet] 45
jenže [but/only] 4 přitom [at the same time] 31 sice - však [although - yet] 37

5 most common discourse connectives: reason-result

proto [therefore] 31 proto [therefore] 301 protože [because] 510
tedy [thus] 25 totiž [namely/you see] 285 nebot’ [for] 212
totiž [namely/you see] 21 tedy [thus] 142 takže [so] 116
a tak [and so] 6 tak [so] 66 a tak [and so] 95
v tomto směru [in this sense] 5 a tak [and so] 34 proto, že [because] 95

Table 8: The most common discourse connectives for conjunction, opposition, and reason-result
(number of occurrences)

mostly differ in the direction of the reason-result relation which influences the choice of the dis-
course connectives. While inter-sentential relations mainly express the meaning of result (discourse
connectives proto [therefore], tedy [thus], a tak [and so], v tomto směru [in this sense]), intra-
sentential relations more typically represent the meaning of reason (discourse connectives protože
[because], nebot’ [for], proto, že [because]).

Generally, there is a certain difference among the observed datasets in the usage of secondary
connectives. Whereas in intra-sentential relations (dataset 3) secondary connectives do not occur
in high positions of the table, they are yet frequent enough in the dataset 2 (dodal [he added]) and
even more in the dataset 1 (dodal [he added], v tomto směru [in this sense]).

To sum up, discourse connectives in the cross-paragraph and local coherence overlap to a large
extent; nevertheless, paragraph-initial discourse connectives still have some special features. Some
of them are based on the inter-sentential character of cross-paragraph relations and they are common
for datasets (1) and (2). Thus, discourse connectives in these groups do not include relative elements
or typical intra-sentential expressions (sice [true/sure]). Further, in the inter-sentential context,
discourse connectives expressing result are used more often than connectives of reason. The latter
are, on the other hand, more frequent in the intra-sentential relations (dataset 3).

Within the group of inter-sentential discourse connectives (datasets 1 and 2), paragraph-initial
connectives differ from intra-paragraph connectives in certain aspects. For the relation of conjunc-
tion, the specific discourse connective dále [further, next] is frequently used. The proportion of
secondary discourse connectives is higher in this group than in datasets (2 and 3), too.

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POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

Left Arg size Right Arg size Count Percent
(no. of sentences) (no. of sentences)

1 1 5 966 89.1%
1 large 92 1.4%

large 1 617 9.2%
large large 20 0.3%

total 6 695 100%

Table 9: Overview of argument sizes of inter-sentential discourse relations without lists in PDiT 2.0.

4.4 Large arguments

Although the minimality principle was taken into account during annotating argument extents in the
PDiT, the annotators could also mark large argument spans and non-adjacent arguments, if justified
(compare 4.2). In a way, the minimality principle, if applied thoroughly, can prevent the detection of
natural “whole paragraph” to “whole paragraph” relations and similar. In this part of the analysis, we
try to look into cases where marking a large argument was superior to the minimality requirement,
we quantify them and try to find explanations for them.

For this study, relations with large arguments are specified as relations where either one or
both arguments are larger than one sentence. For the analysis, we only take into account explicit
inter-sentential relations and exclude list structures. We also exclude such intra-sentential relations,
which cross the sentence boundary with a part of one of their arguments. They represent a very
specific group (25 instances in the corpus).

In the data of the PDiT 2.0, extents of discourse arguments are given by the tree representation
of a sentence – a discourse relation is marked between two tree nodes, roots of two subtrees that in
most cases represent the arguments – and further specified by two range attributes, start_range
and target_range, which help define more complex cases. It is important to keep in mind that
for symmetric relations (i.e. where both arguments are of the same nature and the linear order of
the arguments is always the same, as in conjunction, opposition or synchrony), the target_range
attribute value always defines the extent of the left-sided argument and the start_range attribute
value defines the extent of the right-sided argument. For asymmetric relations like reason-result, in
which the arguments can switch the order, start- and target range are assigned to each relation indi-
vidually via semantic definitions of Arg1 and Arg2. Arg1 always has the target_range attribute,
disregarding its location. This property of the PDiT annotation needs to be taken into account in the
phase of the analysis below where the left or right position of the arguments matter.23

The proportions of inter-sentential relations with different sizes of arguments are summarized
in Table 9. There are 5 966 relations with single-sentenced both arguments in the PDiT 2.0, in other
words relations with “small” arguments, and they represent 89% of all inter-sentential relations.

23. The target arguments (Arg1) are the following for asymmetric relations: (pragm.) result for the relation(s) of (pragm.)
reason-result, statement being explained (explication), result of a (pragm.) condition ((pragm.) condition), denial of
expectation (concession), statement being corrected (correction), statement having a purpose (purpose), lower degree
(gradation), successive event (precedence-succession), statement being restricted/having an exception (restr. opposi-
tion), more general statement (instantiation, specification), more specific statement (generalization). For symmetric
relations, target argument (Arg1) is always the left-sided argument.

22


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

Left Arg - Right Arg Start (Arg2) - Target (Arg1)

Relation Total Large Left Large Right Both Large Large Start Large Target Both Large

concession 29 27 1 1 23 5 1
condition 3 3 0 0 2 1 0
confrontation 39 35 2 2 2 35 2
conjunction 115 107 4 4 4 107 4
conj. alternative 2 1 1 0 1 1 0
correction 6 5 0 1 0 5 1
equivalence 11 8 0 3 0 8 3
instantiation 21 6 13 2 13 6 2
explication 23 7 14 2 15 6 2
generalization 78 76 2 0 2 76 0
gradation 13 10 2 1 2 10 1
opposition 173 158 12 3 12 158 3
pragm. contrast 3 2 1 0 1 2 0
pragm. reason-result 6 6 0 0 3 3 0
precedence-succession 9 9 0 0 9 0 0
reason-result 176 139 36 1 155 20 1
restr. opposition 13 12 1 0 1 12 0
specification 3 0 3 0 3 0 0
synchrony 6 6 0 0 0 6 0

total 729 617 92 20 248 461 20

Table 10: Large arguments in PDiT 2.0, measured both for the left-right positions and start-range
target-range directions (= semantics of the arguments); "large" means that the given ar-
gument spans more than one sentence while the other one (in the same column) only
spans one sentence (of its subset); symmetric relations are marked with the light gray
background.

The remaining 729 relations that have at least one large argument (two and more sentences), form
11% of all inter-sentential relations. There are 617 relations with a large left argument and a single-
sentenced right argument (large – 1), compared to only 92 relations with large right argument and
a single-sentenced left argument (1 – large). There are only 20 relations with both large arguments
(large – large), which is, given the figures for hierarchies, in our opinion a surprisingly low number,
in terms of percentage negligible.

The most distinctive finding for large arguments is the huge disproportion of left-sided and right-
sided large arguments, or in other words, the great predominance of large left-sided arguments.
In a detailed view, the figures in Table 10, the “left - right” section, show that this is the case
across almost all discourse types (senses).24 However, the left-right positions of the arguments are
only informative for symmetric relations (with grey background in Table 10), we will elaborate on

24. In our data, three relations, disjunctive alternative, pragm. condition and purpose do not have any instances with
large arguments.

23


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

them further in this section.25 For asymmetric relations, argument semantics plays a crucial role.
There are three exceptions to the tendency of a larger left-sided argument in Table 10: instantiation,
explication and specification, where large right-sided arguments are more common. But, if we look
at the “start-target” part of the table, which is more informative for these asymmetric relations,
we can see that in all these cases, argument semantics goes hand in hand: these are precisely the
relations where the right contexts are represented by those arguments, which are easily conceivable
as more elaborated, expandable: the argument providing an explanation (large start arg = 15), the
argument giving example (13), the specifying argument (3).26 For comparison, an analogous, and
in terms of numbers much stronger, disproportion is visible in generalization, also an asymmetric
relation, with 76 large left contexts which are also the 76 more specific arguments. The figures here
fully comply with the intuitive notions of how semantics of these relations work, e.g. a generalizing,
summarizing statement should be generalizing over a large previous text segment.

What could be less intuitive are the sizes of individual arguments in reason-result relation.
For this relatively frequent relation,27 (176 instances with large arguments in total), 155 (88%)
have a large “reason” arguments but only 20 (11%) have a large “result” argument. The large
arguments stand mostly on the left. Thus, semantically, the arguments are in line with the similar
explication relation, that means the dominance of large reason/explication arguments, but in terms
of location, these arguments stand elsewhere, on the left for reason-result and on the right for
explication. A possible explanation can be the different importance of the arguments, in the terms
of RST nuclearity, and/or role of secondary connectives and connective phrases.

For symmetric relations, we do not have a straighforward explanation for the predominance of
large left-sided arguments. Only the following assumptions can be suggested: we might evaluate
this as an effect of the annotation strategy, given that the connective is mostly a part of the right-sided
argument, and so it may seem unnatural to go beyond the strong right boundary of the connective-
containing sentence. We may also ask if the minimality principle is applied the same way to left
and right contexts. And/or, this phenomenon might be inherent to language. In a similar manner in
which anaphora in the language occurs much more often than cataphora, the connectives (some of
which are indeed anaphoric, compare Webber et al. (2003), Stede and Grishina (2016) or Poláková
and Mírovský (2019)), relate to small or larger previous semantic contents.28 From a cognitive
perspective, this disproportion of argument sizes may be connected with the linear way of text
production and also the gradual growth of information received by the reader, and the perspective
of the annotator, who may proceed incrementally, like a reader, not knowing about the sizes of any
right context. This issue needs a further insight, since it may be very important for the understanding
of the difference of analytic perspectives in local and global annotation approaches.

25. This also implies that proportions of numbers for symmetric relations in the left-right section and the start-target
section of Table 10 are identical, they only reflect the annotation convention that the target argument is always on the
left, in other words, the discourse arrow always leads to the left for the symmetric relations.

26. Counts for these three relations are too low to draw any hard conclusion but even the small numbers here support the
intuitive claims.

27. Even when its intra-sentential instances are filtered out here, there are no protože [because]-relations included.
28. In our experience, cataphoric connectives are mostly secondary, with a demonstrative element that mostly introduces

a dependent clause (e. g. thanks to the fact that... ) and so their scope is very narrow. This might be, however,
language-specific.

24


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

5. Conclusion

The aim of this study was to determine, using corpus methods, to what extent local annotations of
discourse relations enable to abstract and describe phenomena of global coherence or higher text
structuring. We used the 50 thousand sentences of the Prague Discourse Treebank 2.0 for Czech
and the equally sized Penn Discourse Treebank 3 for English.29 The analysis focused on three main
aspects: 1. the “shape” of the text in terms of mutual configuration of close discourse relations
(pairwise); 2. cross-paragraph relations, their semantics and the properties of connectives in these
relations as opposed to intra-paragraph settings, and 3. the size of arguments (text units) connected
by discourse relations.

Regarding 1., even the discourse relations annotated in local annotations settings are assumed to
form specific patterns, which are inherent in global coherence models like the Rhetorical Structure
Theory (RST), but not postulated for local coherence models. This includes recursive hierarchical
structuring of smaller and larger relations. Also, the RST model applies strong constraints on the
overall document structure, defining it as a (constituency) tree with no crossings and overlaps.

Our analysis of relation configurations further contributes to the theoretical coherence-oriented
research in particular by bringing empirical data to the discussion whether RST tree graphs are
adequate (and sufficient) to represent discourse structure: Czech data available to us support this
claim, exceptions are very rare. We have described patterns that are typical (adjacency, progress,
hierarchy, etc.), less typical (argument containment patterns, envelopment) and quite rare (total
overlap, crossing, partial overlaps etc.) in our data, and analyzed them linguistically. Further, we
have compared our findings to those of a similar study conducted on English PDTB, version 2 (Lee
et al., 2006), learning that the proportions of occurrence of individual patterns roughly correspond in
both corpora, although our study distinguishes some more subtle configurations. Frequent patterns
in our data comply with the RST tree structure rules. Less frequent patterns in the PDiT mostly deal
with inclusion or exclusion of attribution spans, but also with the annotation strategies for secondary
connectives in cases where they form a whole clause (It means that...) or they are anaphoric (in this
respect). In some rare patterns, where, in our opinion, there is a violation of the tree structure in the
sense of RST, we have found a small number of linguistically defensible interpretations that are not
to be factored out due to discourse anaphora or attribution, as Lee et al. (2006) suggest.

Next, we have investigated hierarchies built by nested local relations in both Czech and English
data. In all investigated properties in this respect, the two corpora are very similar. In both of them,
we have detected even 5-level hierarchies, although they are quite rare. In a more detailed perspec-
tive, however, much of the structure proved to be intra-sentential: beyond the sentence boundary,
local annotation of explicit connectives and AltLexes does not expose hierarchical text structuring
very often. Detected hierarchies of inter-sentential relations only reached max. 3 levels of depth
in both corpora. We do not claim that the trees detected by us are the trees a global analysis like
RST would discover, but we demonstrate the existence of some hierarchical text structure in local
annotation.

2. In the part of the analysis concerning cross-paragraph phenomena, the distributions of seman-
tic types of discourse relations reveal dominance of three elaborative meanings, namely specifica-
tion, generalization, and instantiation in relations crossing the paragraph boundary. These relations

29. The analysis of English locally annotated data is so far only complementary to the analyses of Czech data but we
plan to extend it also to other subtopics in this study in the future.

25


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

are not in the top ten most frequent of all other intra-paragraph relations,30 and our findings only
confirm their intuitively perceived large role in text composition and lesser role in syntax.

Nevertheless, it was observed that the feature of inter/intra-sententiality is more important for
the semantics of discourse relations than the presence or absence of the paragraph boundary. Typical
intra-sentential relations, such as condition, purpose, disjunctive alternative and synchrony, almost
never occur in cross-paragraphs relations in our data.

As for connectives, for the relation of conjunction, there seems to exist a specific discourse con-
nective of cross-paragraph links, the connective dále [further, next]. Distributions of other connec-
tives in frequent relations between and within paragraphs do not vary much, and, counter-intuitively,
also coordinating conjunctions (and, but) are fairly represented in cross-paragraph relations. The
proportion of secondary discourse connectives is higher in these contexts.

3. The analysis of argument size examined the hypothesis that in local coherence models, exis-
tence of large arguments (more than one sentence) should be limited by the annotation principle to
annotate minimal units. It was discovered that relations with one or both large arguments are indeed
not very frequent in PDiT 2.0 (11% of all inter-sentential relations) and that the large argument is
in almost 85% on the left, which might be annotator’s bias when proceeding from left (known con-
text) to right (unknown context), and/or it may an inherent property of texts. It would be interesting
to compare this observation to the ways of tree branching in the RST-Discourse Treebank global
annotations.

In the future, we plan to further extend our analysis to the PDTB 3 data and we would like to
include also implicit relations, entity-based relations and hypophora (relations of question and an-
swer) in both languages. Implicitness is an important feature of inter-sentential discourse relations,
therefore inclusion of implicit relations into the research will enhance the general picture of the dis-
tribution of semantic types. This kind of results can be used then e.g. for the prediction of meaning
of inter-sentential discourse relations. Furthermore, the role of the typically implicit semantic types,
such as instantiation or specification, can be described in detail in this way.

The outcome of the study will be reflected in a future RST-like annotation of Czech. First, the
results will be confronted with a real pilot RST analysis on a sample of locally annotated Czech
texts with detected hierarchical organization, in order to assess the degree of equivalence of the
hierarchical structures. The findings about hierarchies and the large arguments from this study can
be further crosschecked with notions like nuclearity and canonical order of discourse arguments to
find more about possible bridging through global and local frameworks. Also, the distribution of
semantic labels given the size of text arguments in local annotations can be related to the use of
RST labels (e.g. to the division to subject matter and presentational rhetorical relations) and their
correspondence in lower and higher structuring can be discussed.

The fact that local discourse annotation in both PDiT and PDTB also displays hierarchical struc-
ture (up to 5 levels of depth) but at least two lowest levels are usually intra-sentential, implies a large
role of syntax in discourse complexity. Syntactic hypotaxis/parataxis, but also the (a)symmetry of
local discourse labels when related to nuclearity can be of advantage in a possible automatic RST
pre-annotation or in rhetorical parsing.

Last but not least, methodologically, our experiments seem to reveal a lot about annotation
strategies and biases: the minimality principle seems to affect the left-sided and right-sided argu-
ment sizes with great difference and its consistent application also may hinder the ability of local

30. with the sole exception of specification in intra-sentential use, which may be connected to the very frequent nominal
right-sided arguments (and governing verb ellipsis) in the PDiT annotaiton.

26


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

models to accurately assess coherence of larger blocks. Our results also open space for the hypoth-
esis that the annotation procedure itself, e.g. the order in which individual segments are connected
to other segments, may influence the segment size and the hierarchical structure formed.

Acknowledgements

The authors would like to thank three anonymous reviewers for their detailed and constructive com-
ments. The authors acknowledge support from the and the Grant Agency of the Czech Republic
(project no. 20-09853S). The research reported in the present contribution has been using language
resources developed, stored and distributed by the LINDAT/CLARIAH-CZ project of the Ministry
of Education, Youth and Sports of the Czech Republic (project no. LM2018101).

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https://link.springer.com/chapter/10.1007/978-3-030-27947-9_20


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

Appendix 1: A four-level hierarchy in Prague Discourse Treebank 2.0

A Czech original and an English translation of a PDiT 2.0 text segment (cmpr9410_034, 1.5 para-
graphs, 11 sentences) with a detected 4-level hierarchy of discourse relations.
The pattern of the hierarchy is A ( B ( C ( D ) E ) F G ).

A

FB G

C

D

E

Context:

(1) Přehlídka bezradnosti [paragraph boundary] (2) Z historie je znám nejeden případ, kdy na mistrně vyvedeném padělku

pohořela celá plejáda soudních znalců. (3) Ve 30. letech tohoto století plnila titulní stránky berlínských deníků jedna z

největších afér v historii falzifikátů. (4) Obchodník s obrazy, jakýsi Wacker, byl obviněn, že dodal na výstavu 33 falešných

van Goghů. (5) Skandál brzy přerostl v odbornou polemiku. (6) Obžalovací spis obsahoval několik tisíc stran.

(7) Soud vzal na vědomí názory více než šedesáti uměleckých historiků a kritiků.
(8) Nebyly mezi nimi ani dva, které by se nerozcházely alespoň v podrobnostech.
(9) Každé stanovisko našlo svého zastánce.
(10) Všichni začali být tou přemírou odborníků unaveni.

[paragraph boundary]
(11) Umělecký restaurátor a badatel de Wilt vzbudil v uměleckém světě senzaci, když (D) využil
rentgenové záření k posouzení stáří obrazu.
(12) Jeho závěr zněl, že (C) soubor je starý minimálně tři desetiletí a tudíž pravý.
(13) Nebot’ (E) jaký blázen by měl zájem kolem roku 1895 padělat holandského umělce, jehož
plátna byla k dostání po dvou stech francích?
(14) Obžaloba si též (B) najala znalce, který pracoval s rentgenem.
(15) Ten prozkoumal kolekci z hlediska malířského rukopisu a (F) došel k závěru, že (G) ji nena-
maloval van Gogh.
(16) Soud byl opět tam, kde předtím.
(17) Ani (A) znalci, kteří měli analyzovat obrazy chemickou cestou, nenašli společnou řeč.

Context:

(1) Parade of cluelessness [paragraph boundary] (2) There is more than one case in history in which a wide range of

forensic experts have failed in judging a masterfully executed forgery. (3) In the 30’s of this century, one of the greatest

affairs in the history of falsehoods filled the front pages of Berlin newspapers. (4) A painting dealer, a Wacker, was

accused of supplying 33 fake van Goghs to an exhibition. (5) The scandal soon became a professional controversy.

(6) The indictment file contained several thousand pages.

(7) The court has recorded the views of over 60 art historians and critics.

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DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

(8) There were not two of them that did not diverge at least in detail.
(9) Each opinion found its defender.
(10) Everyone grew weary of the excess of experts.

[paragraph boundary]
(11) The artistic restorer and explorer de Wilt caused a sensation in the world of art when (D) he
used X-rays to assess the age of the painting.
(12) His conclusion was that (C) the collection was at least three decades old and therefore genuine.
(13) For (E) what fool would be interested, circa 1895, in forging a Dutch artist whose canvases
were available at two hundred francs each?
(14) The prosecution also (B) hired an expert to work with the X-ray device.
(15) He examined the collection in terms of the painting’s handwriting and (F) concluded that (G)
it was not painted by van Gogh.
(16) The Court was back where it had been before.
(17) Not even (A) the experts who were to analyze the paintings chemically could find common
ground.

Relation A (‘ani’ [not even], conjunction):

leftarg: (7 - 16) The court has recorded the views of over 60 art historians and critics. There were
not two of them that did not diverge at least in detail. Each opinion found its defender. Everyone
grew weary of the excess of experts.

The artistic restorer and explorer de Wilt caused a sensation in the world of art when he used
X-rays to assess the age of the painting. His conclusion was that the collection was at least three
decades old and therefore genuine. For what fool would be interested, circa 1895, in forging a
Dutch artist whose canvases were available at two hundred francs each? The prosecution also hired
an expert to work with the X-ray device. He examined the collection in terms of the painting’s
handwriting and concluded that it was not painted by van Gogh. The Court was back where it had
been before.

[Soud vzal na vědomí názory více než šedesáti uměleckých historiků a kritiků. Nebyly mezi nimi ani
dva, které by se nerozcházely alespoň v podrobnostech. Každé stanovisko našlo svého zastánce. Všichni
začali být tou přemírou odborníků unaveni.

Umělecký restaurátor a badatel de Wilt vzbudil v uměleckém světě senzaci, když využil rentgenové
záření k posouzení stáří obrazu. Jeho závěr zněl, že soubor je starý minimálně tři desetiletí a tudíž pravý.
Nebot’ jaký blázen by měl zájem kolem roku 1895 padělat holandského umělce, jehož plátna byla k dostání
po dvou stech francích? Obžaloba si též najala znalce, který pracoval s rentgenem. Ten prozkoumal kolekci z
hlediska malířského rukopisu a došel k závěru, že ji nenamaloval van Gogh. Soud byl opět tam, kde předtím.]

rightarg: (17) the experts who were to analyze the paintings chemically could find common ground
[znalci, kteří měli analyzovat obrazy chemickou cestou, nenašli společnou řeč]

Relation B (‘též’ [also], conjunction):

leftarg: (11 - 13) The artistic restorer and explorer de Wilt caused a sensation in the world of
art when he used X-rays to assess the age of the painting. His conclusion was that the collection
was at least three decades old and therefore genuine. For what fool would be interested, circa
1895, in forging a Dutch artist whose canvases were available at two hundred francs each?

33


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

[Umělecký restaurátor a badatel de Wilt vzbudil v uměleckém světě senzaci, když využil rentgenové
záření k posouzení stáří obrazu. Jeho závěr zněl, že soubor je starý minimálně tři desetiletí a tudíž pravý.
Nebot’ jaký blázen by měl zájem je kolem roku 1895 padělat holandského umělce, jehož plátna byla k
dostání po dvou stech francích?]

rightarg: (14) The prosecution hired an expert to work with the X-ray device.
[Obžaloba si najala znalce, který pracoval s rentgenem.]

Relation C (‘Jeho závěr zněl, že’ [His conclusion was that], generalization):

leftarg: (11) The artistic restorer and explorer de Wilt caused a sensation in the world of art
when he used X-rays to assess the age of the painting.

[Umělecký restaurátor a badatel de Wilt vzbudil v uměleckém světě senzaci, když využil rentge-
nové záření k posouzení stáří obrazu.]
rightarg: (sub12)31 the collection was at least three decades old and therefore genuine

[soubor je starý minimálně tři desetiletí a tudíž pravý]

Relation D (‘když’ [when], specification):

leftarg: (sub11) The artistic restorer and explorer de Wilt caused a sensation in the world
of art

[Umělecký restaurátor a badatel de Wilt vzbudil v uměleckém světě senzaci]
rightarg: (sub11) he used X-rays to assess the age of the painting

[využil rentgenové záření k posouzení stáří obrazu]

Relation E (‘nebot’’ [for], reason – result):

leftarg: (sub12) (it is) genuine
[je pravý]32

rightarg: (13) what fool would be interested, circa 1895, in forging a Dutch artist whose
canvases were available at two hundred francs each

[jaký blázen by měl zájem kolem roku 1895 padělat holandského umělce, jehož plátna byla k
dostání po dvou stech francích]

Relation F (‘a’ [and], conjunction):

leftarg: (sub15) examined the collection in terms of the painting’s handwriting
[prozkoumal kolekci z hlediska malířského rukopisu]

rightarg: (sub15) concluded that it was not painted by van Gogh
[došel k závěru že ji nenamaloval van Gogh]

Relation G (‘došel k závěru’ [concluded that], generalization):

leftarg: (sub15) He examined the collection in terms of the painting’s handwriting
[prozkoumal kolekci z hlediska malířského rukopisu]

rightarg: (sub15) it was not painted by van Gogh
[ji nenamaloval van Gogh]

31. "sub" refers to the fact that the argument includes only a subset of a given sentence, not the whole sentence.
32. verb ellipsis restored from the previous clause via generated node in the tree structure

34


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

Appendix 2: A five-level hierarchy in the Penn Discourse Treebank 3.0

The PDTB 3.0 text segment (wsj_2431, 2 paragraphs, 7 sentences) with a detected 5-level hierarchy
of discourse relations. The pattern of the hierarchy is A ( B C D ( E ( F ( G )))).33

A

CB D

E

F

G

Context:
(21) The coalition government tried to show that PASOK ministers had received hefty sums for OKing the purchase

of F-16 Fighting Falcon and Mirage 2000 combat aircraft, produced by the U.S.based General Dynamics Corp. and

France’s Avions Marcel Dassault, respectively. (22) Naturally, neither General Dynamics nor Dassault could be expected

to hamper its prospective future dealings by making disclosures of sums paid (or not ) to various Greek officials for

services rendered.

(23) So it seems that Mr. Mitsotakis and his communist chums may have unwittingly served Mr.
Papandreou a moral victory on a platter: PASOK, whether guilty or not, can now traipse the coun-
tryside condemning the whole affair as a witch hunt at Mr. Papandreou’s expense.
(24) But (B) while (C) verbal high jinks alone won’t help PASOK regain power, Mr. Papandreou
should never be underestimated.
(25) First came his predictable fusillade: He charged the Coalition of the Left and Progress had
sold out its leftist tenets by (F) collaborating in a right-wing plot aimed at ousting PASOK and (G)
thwarting the course of socialism in Greece.

[paragraph boundary]

(26) Then (E), to buttress his credibility with the left, he enticed some smaller leftist parties to stand
for election under the PASOK banner.
(27) Next (D), he continued to court the communists – many of whom feel betrayed by the left-right
coalition’s birth – by bringing into PASOK a well-respected Communist Party candidate.
(28) For balance, and in hopes of gaining some disaffected centrist votes, he managed to attract a
former New Democracy Party representative and known political enemy of Mr. Mitsotakis.
(29) Thus (A) PASOK heads for the polls not only with diminished scandal-stench, but also with
“seals of approval” from representatives of its harshest accusers.

33. Note that the relations B and C do not take part in the deepest branch of the hierarchy, they are only included in the
higher relation A.

35


POLÁKOVÁ, MÍROVSKÝ, ZIKÁNOVÁ AND HAJIČOVÁ

Relation A (‘thus’, Contingency.Cause.Result):

leftarg: (23 - 28) So it seems that Mr. Mitsotakis and his communist chums may have unwittingly
served Mr. Papandreou a moral victory on a platter: PASOK, whether guilty or not, can now traipse
the countryside condemning the whole affair as a witch hunt at Mr. Papandreou’s expense. But
while verbal high jinks alone won’t help PASOK regain power, Mr. Papandreou should never be
underestimated. First came his predictable fusillade: He charged the Coalition of the Left and
Progress had sold out its leftist tenets by collaborating in a right-wing plot aimed at ousting PASOK
and thwarting the course of socialism in Greece.

Then, to buttress his credibility with the left, he enticed some smaller leftist parties to stand for
election under the PASOK banner. Next, he continued to court the communists – many of whom feel
betrayed by the left-right coalition’s birth – by bringing into PASOK a well-respected Communist
Party candidate. For balance, and in hopes of gaining some disaffected centrist votes, he managed to
attract a former New Democracy Party representative and known political enemy of Mr. Mitsotakis.
rightarg: (29) PASOK heads for the polls not only with diminished scandal-stench, but also with
“seals of approval” from representatives of its harshest accusers

Relation B (‘but’, Comparison.Concession.Arg2-as-denier):

leftarg: (sub23) PASOK, whether guilty or not, can now traipse the countryside condemning the
whole affair as a witch hunt at Mr. Papandreou ’s expense
rightarg: (24) while verbal high jinks alone wo n’t help PASOK regain power, Mr. Papandreou
should never be underestimated

Relation C (‘while’, Temporal.Synchronous):

leftarg: (sub24) But... Mr. Papandreou should never be underestimated
rightarg: (sub24) verbal high jinks alone won’t help PASOK regain power

Relation D (‘next’, Temporal.Asynchronous.Precedence):

leftarg: (25 - 26) First came his predictable fusillade: He charged the Coalition of the Left and
Progress had sold out its leftist tenets by collaborating in a right-wing plot aimed at ousting
PASOK and thwarting the course of socialism in Greece.

Then, to buttress his credibility with the left, he enticed some smaller leftist parties to stand
for election under the PASOK banner
rightarg: (sub27) he continued to court the communists ... by bringing into PASOK a well-
respected Communist Party candidate

Relation E (‘then’, Temporal.Asynchronous.Precedence):

leftarg: (sub25) He charged the Coalition of of the Left and Progress had sold out its leftist
tenets by collaborating in a right wing plot aimed at ousting PASOK and thwarting the course
of socialism in Greece
rightarg: (sub26) he enticed some smaller leftist parties to stand for election under the PA-
SOK banner

Relation F (‘by’, Contingency.Cause.Reason):

leftarg: (sub25) the Coalition of the Left and Progress had sold out its leftist tenets

36


DISCOURSE RELATIONS AND CONNECTIVES IN HIGHER TEXT STRUCTURE

rightarg: (sub25) collaborating in a right-wing plot aimed at ousting PASOK and thwart-
ing the course of socialism in Greece

Relation G (‘and’, Expansion.Conjunction):

leftarg: (sub25) ousting PASOK
rightarg: (sub25) thwarting the course of socialism in Greece

37


	Introduction
	Goals
	Theoretical Aspects and Definitions

	Related Research
	Rhetorical Structure Theory
	Penn Discourse Treebank

	Data and Tools
	Analysis
	Configurations of Close Relation Pairs
	Hierarchies
	Hierarchies in the PDiT 2.0
	Hierarchies in the Penn Discourse Treebank 3.0

	Paragraph-initial Semantic Types and Connectives
	Discourse connectives in paragraph-initial positions

	Large arguments

	Conclusion