Discourse structure and language technology

Webber, Bonnie; Egg, Markus; Kordoni, Valia

doi:10.1017/s1351324911000337

Cited by 84 publications

(54 citation statements)

References 84 publications

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“…sentences, clauses or nominalizations (Webber et al, 2012). Often, the text units considered in discourse analysis correspond to argument components, and discourse relations are closely related to argumentative relations.…”

Section: Related Workmentioning

confidence: 99%

Linking the Thoughts: Analysis of Argumentation Structures in Scientific Publications

Kirschner¹,

Eckle‐Kohler²,

Gurevych³

2015

Proceedings of the 2nd Workshop on Argumentation Mining

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This paper presents the results of an annotation study focused on the fine-grained analysis of argumentation structures in scientific publications. Our new annotation scheme specifies four types of binary argumentative relations between sentences, resulting in the representation of arguments as small graph structures. We developed an annotation tool that supports the annotation of such graphs and carried out an annotation study with four annotators on 24 scientific articles from the domain of educational research. For calculating the inter-annotator agreement, we adapted existing measures and developed a novel graphbased agreement measure which reflects the semantic similarity of different annotation graphs.

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Section: Related Workmentioning

confidence: 99%

Linking the Thoughts: Analysis of Argumentation Structures in Scientific Publications

Kirschner¹,

Eckle‐Kohler²,

Gurevych³

2015

Proceedings of the 2nd Workshop on Argumentation Mining

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“…An example is the segmentation of scientific papers into functional segments and their labeling with categories such as BACKGROUND and DISCUSSION (Liakata et al, 2010). See (Webber et al, 2011) for a survey of discourse structure in NLP.…”

Section: Semantic Contentmentioning

confidence: 99%

The State of the Art in Semantic Representation

Abend¹,

Rappoport²

2017

Proceedings of the 55th Annual Meeting of the Association For Computational Linguistics (Volume 1: Long Papers)

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Semantic representation is receiving growing attention in NLP in the past few years, and many proposals for semantic schemes (e.g., AMR, UCCA, GMB, UDS) have been put forth. Yet, little has been done to assess the achievements and the shortcomings of these new contenders, compare them with syntactic schemes, and clarify the general goals of research on semantic representation. We address these gaps by critically surveying the state of the art in the field.

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“…Previous efforts to overcome this issue have looked at discourse indicators [53] -explicit linguistic expressions signalling the discursive role played by an utterance [49] -as easily identified patterns that require no prior annotation [26,55]. Whilst discourse indicators have been shown to be a reliable way of determining argumentative structure, the majority of arguments is not explicitly signalled by means of such an indicator, limiting their effectiveness in argument mining.…”

Section: Argument Miningmentioning

confidence: 99%

Harnessing rhetorical figures for argument mining

Lawrence

Visser

Reed

2017

AAC

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Abstract. The generalised, automated reconstruction of the reasoning structures underlying persuasive communication is an enormously challenging task. While this work in argument mining is increasingly informed by the rich tradition of argumentation studies outside the computational field, the rhetorical perspective on argumentation is thus far largely ignored. To explore the application of rhetorical insights in argument mining, we conduct a pilot study on the connection between rhetorical figures and argumentation structure. Rhetorical figures are linguistic devices that perform a variety of functions in argumentative discourse. The textual form of some of these figures is easy to identify automatically, such that an established connection between the figure and a preponderance of argumentative content would improve the performance of argument mining techniques. Furthermore, the automated mining of rhetorical figures could be used as an empirical, corpus-based testing ground for the claims made about these figures in the rhetorical literature. In the pilot study, we explore the connection between eight rhetorical figures the forms of which we expect to be relatively easy to identify computationally, and argumentation structure (concretely, we consider the six schemes 'anadiplosis', 'epanaphora', 'epistrophe', 'epizeuxis', 'eutrepismus', and 'polyptoton', and the two tropes 'antithesis' and 'dirimens copulatio', and relate their occurrences to relations of inference and conflict). The data of the study is collected in the MM2012c corpus of 39,694 words of argumentatively annotated transcripts from the BBC Radio 4's Moral Maze discussion program. We show that some of the figures indeed correspond to passages of high argumentative density, relative to the text as a whole.

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Discourse structure and language technology

Cited by 84 publications

References 84 publications

Linking the Thoughts: Analysis of Argumentation Structures in Scientific Publications

Linking the Thoughts: Analysis of Argumentation Structures in Scientific Publications

The State of the Art in Semantic Representation

Harnessing rhetorical figures for argument mining

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