Signalling Implicit Relations: A PDTB - RST Comparison

Poláková, Lucie; Mírovský, Jiří; Synková, Pavlína

doi:10.5087/dad.2017.210

Cited by 7 publications

(5 citation statements)

References 16 publications

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“…They found that their empirical results matched the theoretical mappings in more than 70% of the explicit relations, but only in less than 50% of the implicit relations. Another empirical mapping between the RST-DT and the PDTB 2.0 corpora was conducted by Polakova et al (2017). They focused only on implicit discourse relations where an exact segment span matching was possible, which included a total of 472 discourse relations.…”

Section: Previous Workmentioning

confidence: 99%

Mapping Explicit and Implicit Discourse Relations between the RST-DT and the PDTB 3.0

Costa,

Sheikh,

Kosseim

2023

Proceedings of the Conference Recent Advances in Natural Language Processing - Large Language Models for Natural Language Proce

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In this paper we propose a first empirical mapping between the RST-DT and the PDTB 3.0. We provide an original algorithm which allows the mapping of 6,510 (80.0%) explicit and implicit discourse relations between the overlapping articles of the RST-DT and PDTB 3.0 discourse annotated corpora. Results of the mapping show that while it is easier to align segments of implicit discourse relations, the mapping obtained between the aligned explicit discourse relations is more unambiguous.

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Section: Previous Workmentioning

confidence: 99%

Mapping Explicit and Implicit Discourse Relations between the RST-DT and the PDTB 3.0

Costa,

Sheikh,

Kosseim

2023

Proceedings of the Conference Recent Advances in Natural Language Processing - Large Language Models for Natural Language Proce

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“…A unified framework may provide a common ground for exploring the relations of different frameworks and validating annotation consistency of a corpus. We can perform comparative corpus analysis and obtain new understanding of how information expressed in one framework is conveyed in another framework, thus validating corpus annotation consistency and finding some clues for solving problems in a framework with signals from another framework, similar to Poláková et al (2017) and Bourgonje and Zolotarenko (2019).…”

Section: Introductionmentioning

confidence: 95%

Towards Unification of Discourse Annotation Frameworks

Fu¹

2022

Preprint

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Discourse information is difficult to represent and annotate. Among the major frameworks for annotating discourse information, RST, PDTB and SDRT are widely discussed and used, each having its own theoretical foundation and focus. Corpora annotated under different frameworks vary considerably. To make better use of the existing discourse corpora and achieve the possible synergy of different frameworks, it is worthwhile to investigate the systematic relations between different frameworks and devise methods of unifying the frameworks. Although the issue of framework unification has been a topic of discussion for a long time, there is currently no comprehensive approach which considers unifying both discourse structure and discourse relations and evaluates the unified framework intrinsically and extrinsically. We plan to use automatic means for the unification task and evaluate the result with structural complexity and downstream tasks. We will also explore the application of the unified framework in multitask learning and graphical models.

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“…Lit. translation: "Neither here is_concerned a small portion..." 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.…”

Section: Hierarchiesmentioning

confidence: 99%

“…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.…”

Section: Hierarchies In the Penn Discourse Treebank 30mentioning

confidence: 99%

Discourse Relations and Connectives in Higher Text Structure

Poláková¹,

Mírovský²,

Zikánová³

et al. 2021

dad

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The present article investigates possibilities and limits of local (shallow) analysis of discourse coherence 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 distribution 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 arguments in locally annotated data; (ii) as another type of contribution, some new reflections on methodologies of the approaches under scrutiny.

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Signalling Implicit Relations: A PDTB - RST Comparison

Cited by 7 publications

References 16 publications

Mapping Explicit and Implicit Discourse Relations between the RST-DT and the PDTB 3.0

Mapping Explicit and Implicit Discourse Relations between the RST-DT and the PDTB 3.0

Towards Unification of Discourse Annotation Frameworks

Discourse Relations and Connectives in Higher Text Structure

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