Difference between revisions of "Evaluating Answer Extraction for Why-Qa Using Rst-Annotated Wikipedia Texts"
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| − | '''Evaluating Answer Extraction for Why-Qa Using Rst-Annotated Wikipedia Texts''' - scientific work related to Wikipedia quality published in 2007, written by Suzan Verberne. | + | '''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 == | == 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. | + | 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. |
Revision as of 21:27, 19 June 2019
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.
