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Constructing large proposition databases

Exner, Peter LU and Nugues, Pierre LU orcid (2012) The eighth international conference on Language Resources and Evaluation (LREC 2012) p.3836-3839
Abstract
With the advent of massive online encyclopedic corpora such as Wikipedia, it has become possible to apply a systematic analysis to a wide range of documents covering a significant part of human knowledge. Using semantic parsers, it has become possible to extract such knowledge in the form of propositions (predicate―argument structures) and build large proposition databases from these documents. This paper describes the creation of multilingual proposition databases using generic semantic dependency parsing. Using Wikipedia, we extracted, processed, clustered, and evaluated a large number of propositions. We built an architecture to provide a complete pipeline dealing with the input of text, extraction of knowledge, storage, and... (More)
With the advent of massive online encyclopedic corpora such as Wikipedia, it has become possible to apply a systematic analysis to a wide range of documents covering a significant part of human knowledge. Using semantic parsers, it has become possible to extract such knowledge in the form of propositions (predicate―argument structures) and build large proposition databases from these documents. This paper describes the creation of multilingual proposition databases using generic semantic dependency parsing. Using Wikipedia, we extracted, processed, clustered, and evaluated a large number of propositions. We built an architecture to provide a complete pipeline dealing with the input of text, extraction of knowledge, storage, and presentation of the resulting propositions (Less)
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Knowledge Discovery/Representation, Information Extraction, Information Retrieval, Semantics
host publication
Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)
pages
3836 - 3839
publisher
European Language Resources Association
conference name
The eighth international conference on Language Resources and Evaluation (LREC 2012)
conference location
Istanbul, Turkey
conference dates
2012-05-21 - 2012-05-27
external identifiers
  • wos:000323927703147
  • scopus:84973248631
ISBN
978-2-9517408-7-7
language
English
LU publication?
yes
id
8455e9a2-8006-4053-952b-50b1b702d760 (old id 2971919)
alternative location
http://www.lrec-conf.org/proceedings/lrec2012/pdf/452_Paper.pdf
date added to LUP
2016-04-04 11:31:46
date last changed
2022-05-17 04:52:18
@inproceedings{8455e9a2-8006-4053-952b-50b1b702d760,
  abstract     = {{With the advent of massive online encyclopedic corpora such as Wikipedia, it has become possible to apply a systematic analysis to a wide range of documents covering a significant part of human knowledge. Using semantic parsers, it has become possible to extract such knowledge in the form of propositions (predicate―argument structures) and build large proposition databases from these documents. This paper describes the creation of multilingual proposition databases using generic semantic dependency parsing. Using Wikipedia, we extracted, processed, clustered, and evaluated a large number of propositions. We built an architecture to provide a complete pipeline dealing with the input of text, extraction of knowledge, storage, and presentation of the resulting propositions}},
  author       = {{Exner, Peter and Nugues, Pierre}},
  booktitle    = {{Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)}},
  isbn         = {{978-2-9517408-7-7}},
  keywords     = {{Knowledge Discovery/Representation; Information Extraction; Information Retrieval; Semantics}},
  language     = {{eng}},
  pages        = {{3836--3839}},
  publisher    = {{European Language Resources Association}},
  title        = {{Constructing large proposition databases}},
  url          = {{https://lup.lub.lu.se/search/files/5794810/2971925.pdf}},
  year         = {{2012}},
}