14 April 2005 RST Discourse Corpus Lynn Carlson Daniel Marcu Mary Ellen Okurowski.

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Presentation transcript:

14 April 2005 RST Discourse Corpus Lynn Carlson Daniel Marcu Mary Ellen Okurowski

Theory and Phenomena Annotated Framework for annotation: Rhetorical Structure Theory (Mann and Thompson, 1988) Discourse structure of text represented as tree defined as follows: Leaves: text fragments (mainly clauses) that represent elementary discourse units Internal nodes of tree = contiguous text spans Each node characterized by nuclearity: nucleus = more essential unit; satellite = supporting unit Each node characterized by rhetorical relation that holds between two or more non-overlapping, adjacent spans

Sample Text with EDUs: wsj_1111 [Still, analysts don’t expect the buy-back to significantly affect per- share earnings in the short term.] 16 [“The impact won’t be that great,”] 17 [said Graeme Lidgerwood of First Boston Corp.] 18 [This is in part because of the effect] 19 [of having to average the number of shares outstanding,] 20 [she said.] 21 [In addition,] 22 [Mrs. Lidgerwood said,] 23 [Norfolk is likely to draw down its cash initially] 24 [to finance the purchases] 25 [and thus forfeit some interest income.] 26 wsj_1111

Sample Discourse Tree: wsj_1111 (26) *elaboration-object-attribute- embedded +attribution embedded (17) (18) (21) explanation- argumentative consequence- s same-unit elaboration-additional (16) example attribution attribution (19) (20) * purpose (22) (23) (25)(24)

Nature of Rhetorical Relations Attribution: attribution, attribution-negative Background: background, circumstance Cause: cause, result, consequence Comparison: comparison, preference, analogy, proportion Condition: condition, hypothetical, contingency, otherwise Contrast: contrast, concession, antithesis Elaboration: elaboration-additional, elaboration-general-specific Enablement: purpose, enablement Evaluation: evaluation, interpretation, conclusion, comment Explanation: evidence, explanation-argumentative, reason Joint: list, disjunction Manner-Means: manner, means Topic-Comment: problem-solution, question-answer, topic-comment.. Summary: summary, restatement Temporal: temporal-before, temporal-after, temporal-same-time.. Topic Change: topic-shift, topic-drift

Corpus and Annotation Details 385 WSJ articles from Penn Treebank, representing over 176,000 words of text. ~14% were double- tagged. Document length: 31 to 2124 words; average of words Average # EDUs per document:  Average # words per EDU: 8.1. Nature of articles: general news, financial, business, cultural reviews, editorials Intended users: developers of automatic text processing systems

Inter-Annotator Agreement TaggersUnitsSpansNuclear -ity Rela- tions # docsAvg # EDUs A, E A, B A, C A, F A, D

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