Clarifying Underspecified Discourse Relations in Instructional Texts

Discourse relations contribute to the structure of a text and can optionally be realized through explicit connectives such as 'but' and 'while'.But when are these connectives necessary to avoid possible misunderstandings?We investigate this question by first building a corpus of 4,274 text revisions in each of which a connective was explicitly inserted.For a subset of 250 cases, we collect plausibility annotations on other connectives to check whether they would represent suitable alternative relations.The results of this annotation show that several relations are often perceived as plausible in our data.Furthermore, we analyze the extent to which large language models can identify instances with multiple plausible relations as a possible source of misunderstandings.We find that the models predict plausibility of individual connectives with up to 66% accuracy, but they are not reliable in estimating when multiple relations are plausible.

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Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.633
Primary Topic
Discourse Analysis in Language Studies
Type
article
Field-Weighted Citation Impact
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article

Clarifying Underspecified Discourse Relations in Instructional Texts

Berfin Aktaṣ, Michael Roth
Discourse Analysis in Language Studies
article

Clarifying Underspecified Discourse Relations in Instructional Texts

Berfin Aktaṣ, Michael Roth
article en

Abstract

Discourse relations contribute to the structure of a text and can optionally be realized through explicit connectives such as 'but' and 'while'.But when are these connectives necessary to avoid possible misunderstandings?We investigate this question by first building a corpus of 4,274 text revisions in each of which a connective was explicitly inserted.For a subset of 250 cases, we collect plausibility annotations on other connectives to check whether they would represent suitable alternative relations.The results of this annotation show that several relations are often perceived as plausible in our data.Furthermore, we analyze the extent to which large language models can identify instances with multiple plausible relations as a possible source of misunderstandings.We find that the models predict plausibility of individual connectives with up to 66% accuracy, but they are not reliable in estimating when multiple relations are plausible.

Nuremberg University of Music (DE)
Deutsche Forschungsgemeinschaft
Quality Education
Openalex Percentile: Top 80%
Discourse Analysis in Language Studies
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