TY - GEN
T1 - A framework for compiling high quality knowledge resources from raw corpora
AU - Jin, Gongye
AU - Kawahara, Daisuke
AU - Kurohashi, Sadao
PY - 2014
Y1 - 2014
N2 - The identification of various types of relations is a necessary step to allow computers to understand natural language text. In particular, the clarification of relations between predicates and their arguments is essential because predicate - argument structures convey most of the information in natural languages. To precisely capture these relations, wide-coverage knowledge resources are indispensable. Such knowledge resources can be derived from automatic parses of raw corpora, but unfortunately parsing still has not achieved a high enough performance for precise knowledge acquisition. We present a framework for compiling high quality knowledge resources from raw corpora. Our proposed framework selects high quality dependency relations from automatic parses and makes use of them for not only the calculation of fundamental distributional similarity but also the acquisition of knowledge such as case frames.
AB - The identification of various types of relations is a necessary step to allow computers to understand natural language text. In particular, the clarification of relations between predicates and their arguments is essential because predicate - argument structures convey most of the information in natural languages. To precisely capture these relations, wide-coverage knowledge resources are indispensable. Such knowledge resources can be derived from automatic parses of raw corpora, but unfortunately parsing still has not achieved a high enough performance for precise knowledge acquisition. We present a framework for compiling high quality knowledge resources from raw corpora. Our proposed framework selects high quality dependency relations from automatic parses and makes use of them for not only the calculation of fundamental distributional similarity but also the acquisition of knowledge such as case frames.
KW - Case frames
KW - Dependency selection
KW - Knowledge acquisition
UR - http://www.scopus.com/inward/record.url?scp=85021647014&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85021647014&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85021647014
T3 - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014
SP - 109
EP - 114
BT - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014
A2 - Calzolari, Nicoletta
A2 - Choukri, Khalid
A2 - Goggi, Sara
A2 - Declerck, Thierry
A2 - Mariani, Joseph
A2 - Maegaard, Bente
A2 - Moreno, Asuncion
A2 - Odijk, Jan
A2 - Mazo, Helene
A2 - Piperidis, Stelios
A2 - Loftsson, Hrafn
PB - European Language Resources Association (ELRA)
T2 - 9th International Conference on Language Resources and Evaluation, LREC 2014
Y2 - 26 May 2014 through 31 May 2014
ER -