Difference between revisions of "Evaluating Answer Extraction for Why-Qa Using Rst-Annotated Wikipedia Texts"
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Latest revision as of 08:34, 9 June 2020
Authors | Suzan Verberne |
|---|---|
Publication date | 2007 |
Links | Original |
Evaluating Answer Extraction for Why-Qa Using Rst-Annotated Wikipedia Texts - scientific work related to Wikipedia quality published in 2007, written by Suzan Verberne.
Overview
In this paper the research focus is on the task of answer extraction for why-questions. As opposed to techniques for factoid QA, flnding answers to why- questions involves exploiting text structure. Therefore, authors approach the answer extraction problem as a discourse analysis task, using Rhetorical Structure Theory (RST) as framework. Authors evaluated this method using a set of why-questions that have been asked to the online question answering system answers.com with a corpus of answer fragments from Wikipedia, manually annotated with RST structures. The maximum recall that can be obtained by answer extraction procedure is about 60%. Authors suggest paragraph retrieval as supplementary and alternative approach to RST-based answer extraction.
Embed
Wikipedia Quality
Verberne, Suzan. (2007). "[[Evaluating Answer Extraction for Why-Qa Using Rst-Annotated Wikipedia Texts]]". Dublin : Trinity College.
English Wikipedia
{{cite journal |last1=Verberne |first1=Suzan |title=Evaluating Answer Extraction for Why-Qa Using Rst-Annotated Wikipedia Texts |date=2007 |url=https://wikipediaquality.com/wiki/Evaluating_Answer_Extraction_for_Why-Qa_Using_Rst-Annotated_Wikipedia_Texts |journal=Dublin : Trinity College}}
HTML
Verberne, Suzan. (2007). "<a href="https://wikipediaquality.com/wiki/Evaluating_Answer_Extraction_for_Why-Qa_Using_Rst-Annotated_Wikipedia_Texts">Evaluating Answer Extraction for Why-Qa Using Rst-Annotated Wikipedia Texts</a>". Dublin : Trinity College.
