@inproceedings{tateisi-etal-2014-annotation,
title = "Annotation of Computer Science Papers for Semantic Relation Extrac-tion",
author = "Tateisi, Yuka and
Shidahara, Yo and
Miyao, Yusuke and
Aizawa, Akiko",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/461_Paper.pdf",
pages = "1423--1429",
abstract = "We designed a new annotation scheme for formalising relation structures in research papers, through the investigation of computer science papers. The annotation scheme is based on the hypothesis that identifying the role of entities and events that are described in a paper is useful for intelligent information retrieval in academic literature, and the role can be determined by the relationship between the author and the described entities or events, and relationships among them. Using the scheme, we have annotated research abstracts from the IPSJ Journal published in Japanese by the Information Processing Society of Japan. On the basis of the annotated corpus, we have developed a prototype information extraction system which has the facility to classify sentences according to the relationship between entities mentioned, to help find the role of the entity in which the searcher is interested.",
}
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<abstract>We designed a new annotation scheme for formalising relation structures in research papers, through the investigation of computer science papers. The annotation scheme is based on the hypothesis that identifying the role of entities and events that are described in a paper is useful for intelligent information retrieval in academic literature, and the role can be determined by the relationship between the author and the described entities or events, and relationships among them. Using the scheme, we have annotated research abstracts from the IPSJ Journal published in Japanese by the Information Processing Society of Japan. On the basis of the annotated corpus, we have developed a prototype information extraction system which has the facility to classify sentences according to the relationship between entities mentioned, to help find the role of the entity in which the searcher is interested.</abstract>
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%0 Conference Proceedings
%T Annotation of Computer Science Papers for Semantic Relation Extrac-tion
%A Tateisi, Yuka
%A Shidahara, Yo
%A Miyao, Yusuke
%A Aizawa, Akiko
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F tateisi-etal-2014-annotation
%X We designed a new annotation scheme for formalising relation structures in research papers, through the investigation of computer science papers. The annotation scheme is based on the hypothesis that identifying the role of entities and events that are described in a paper is useful for intelligent information retrieval in academic literature, and the role can be determined by the relationship between the author and the described entities or events, and relationships among them. Using the scheme, we have annotated research abstracts from the IPSJ Journal published in Japanese by the Information Processing Society of Japan. On the basis of the annotated corpus, we have developed a prototype information extraction system which has the facility to classify sentences according to the relationship between entities mentioned, to help find the role of the entity in which the searcher is interested.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/461_Paper.pdf
%P 1423-1429
Markdown (Informal)
[Annotation of Computer Science Papers for Semantic Relation Extrac-tion](http://www.lrec-conf.org/proceedings/lrec2014/pdf/461_Paper.pdf) (Tateisi et al., LREC 2014)
ACL