Relational paraphrase acquisition from Wikipedia: The WRPA method and corpus†. (May 2015)
- Record Type:
- Journal Article
- Title:
- Relational paraphrase acquisition from Wikipedia: The WRPA method and corpus†. (May 2015)
- Main Title:
- Relational paraphrase acquisition from Wikipedia: The WRPA method and corpus†
- Authors:
- VILA, M.
RODRÍGUEZ, H.
MARTÍ, M. A. - Abstract:
- <abstract abstract-type="normal"> <title>Abstract</title> <p>Paraphrase corpora are an essential but scarce resource in Natural Language Processing. In this paper, we present the Wikipedia-based Relational Paraphrase Acquisition (WRPA) method, which extracts relational paraphrases from Wikipedia, and the derived WRPA paraphrase corpus. The WRPA corpus currently covers person-related and authorship relations in English and Spanish, respectively, suggesting that, given adequate Wikipedia coverage, our method is independent of the language and the relation addressed. WRPA extracts entity pairs from structured information in Wikipedia applying distant learning and, based on the distributional hypothesis, uses them as anchor points for candidate paraphrase extraction from the free text in the body of Wikipedia articles. Focussing on relational paraphrasing and taking advantage of Wikipedia-structured information allows for an automatic and consistent evaluation of the results. The WRPA corpus characteristics distinguish it from other types of corpora that rely on string similarity or transformation operations. WRPA relies on distributional similarity and is the result of the free use of language outside any reformulation framework. Validation results show a high precision for the corpus.</p> </abstract>
- Is Part Of:
- Natural language engineering. Volume 21:Part 3(2015)
- Journal:
- Natural language engineering
- Issue:
- Volume 21:Part 3(2015)
- Issue Display:
- Volume 21, Issue 3, Part 3 (2015)
- Year:
- 2015
- Volume:
- 21
- Issue:
- 3
- Part:
- 3
- Issue Sort Value:
- 2015-0021-0003-0003
- Page Start:
- 355
- Page End:
- 389
- Publication Date:
- 2015-05
- Subjects:
- Natural language processing (Computer science) -- Periodicals
Software engineering -- Periodicals
006.35 - Journal URLs:
- http://journals.cambridge.org/action/displayJournal?jid=NLE ↗
- DOI:
- 10.1017/S1351324913000235 ↗
- Languages:
- English
- ISSNs:
- 1351-3249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 3846.xml