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Mining Local Discourse Annotation for Features of Global Discourse Structure

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Text, Speech, and Dialogue (TSD 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12284))

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Abstract

Descriptive approaches to discourse (text) structure and coherence typically proceed either in a bottom-up or a top-down analytic way. The former ones analyze how the smallest discourse units (clauses, sentences) are connected in their closest neighbourhood, locally, in a linear way. The latter ones postulate a hierarchical organization of smaller and larger units, sometimes also represent the whole text as a tree-like graph. In the present study, we mine a Czech corpus of 50k sentences annotated in the local coherence fashion (Penn Discourse Treebank style) for indices signalling higher discourse structure. We analyze patterns of overlapping discourse relations and look into hierarchies they form. The types and distributions of the detected patterns correspond to the results for English local annotation, with patterns not complying with the tree-like interpretation at very low numbers. We also detect hierarchical organization of local discourse relations of up to 5 levels in the Czech data.

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Notes

  1. 1.

    In this study, we use the term discourse relations, according to the Penn Discourse Treebank’s terminology.

  2. 2.

    Both ways of text analysis for the same data are rare, yet they exist, e.g. for English Wall Street Journal texts  [2, 13, 18] and for German news commentaries  [14]. For German, even a mapping procedure between the two annotation layers was introduced in  [15].

  3. 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.

  4. 4.

    Due to the limited range of this paper, we only compare our results to theirs for discourse relations. The implications for syntax (level of complexity) is not explicitly discussed.

  5. 5.

    Technically, the annotation is not carried out on raw texts, but on top of the syntactic trees.

  6. 6.

    We have obtained so much data that we must only select certain aspects for this study. We therefore concentrate on the patterns studied by Lee et al., and on hierarchical structuring of discourse relations.

  7. 7.

    Due to space limit we only present the English translations of the PDT Czech originals here. Relation 1 is highlighted in italics, relation 2 in bold. The connectives are underlined.

  8. 8.

    In the representation in Example 2, the clause This means that is not in italics, not a part of any argument of the left relation.

  9. 9.

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

  10. 10.

    This also explains the zeros in Table 2.

  11. 11.

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

References

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Acknowledgments

The authors gratefully acknowledge support from the Grant Agency of the Czech Republic, project no. 20-09853S. The work described herein has been using resources provided by the LINDAT/CLARIAH-CZ Research Infrastructure, supported by the Ministry of Education, Youth and Sports of the Czech Republic (project no. LM2018101).

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Authors and Affiliations

  1. Faculty of Mathematics and Physics, Charles University, Malostranské náměstí 25, 118 00, Prague, Czech Republic

    Lucie Poláková & Jiří Mírovský

Authors
  1. Lucie Poláková
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  2. Jiří Mírovský
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Correspondence to Lucie Poláková .

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Editors and Affiliations

  1. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Petr Sojka

  2. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Ivan Kopeček

  3. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Karel Pala

  4. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Aleš Horák

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Poláková, L., Mírovský, J. (2020). Mining Local Discourse Annotation for Features of Global Discourse Structure. In: Sojka, P., Kopeček, I., Pala, K., Horák, A. (eds) Text, Speech, and Dialogue. TSD 2020. Lecture Notes in Computer Science(), vol 12284. Springer, Cham. https://doi.org/10.1007/978-3-030-58323-1_5

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  • DOI: https://doi.org/10.1007/978-3-030-58323-1_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58322-4

  • Online ISBN: 978-3-030-58323-1

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