@inproceedings{iftene-balahur-dobrescu-2008-named,
title = "Named Entity Relation Mining using {W}ikipedia",
author = "Iftene, Adrian and
Balahur-Dobrescu, Alexandra",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2008/pdf/192_paper.pdf",
abstract = "Discovering relations among Named Entities (NEs) from large corpora is both a challenging, as well as useful task in the domain of Natural Language Processing, with applications in Information Retrieval (IR), Summarization (SUM), Question Answering (QA) and Textual Entailment (TE). The work we present resulted from the attempt to solve practical issues we were confronted with while building systems for the tasks of Textual Entailment Recognition and Question Answering, respectively. The approach consists in applying grammar induced extraction patterns on a large corpus - Wikipedia - for the extraction of relations between a given Named Entity and other Named Entities. The results obtained are high in precision, determining a reliable and useful application of the built resource.",
}
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<abstract>Discovering relations among Named Entities (NEs) from large corpora is both a challenging, as well as useful task in the domain of Natural Language Processing, with applications in Information Retrieval (IR), Summarization (SUM), Question Answering (QA) and Textual Entailment (TE). The work we present resulted from the attempt to solve practical issues we were confronted with while building systems for the tasks of Textual Entailment Recognition and Question Answering, respectively. The approach consists in applying grammar induced extraction patterns on a large corpus - Wikipedia - for the extraction of relations between a given Named Entity and other Named Entities. The results obtained are high in precision, determining a reliable and useful application of the built resource.</abstract>
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%0 Conference Proceedings
%T Named Entity Relation Mining using Wikipedia
%A Iftene, Adrian
%A Balahur-Dobrescu, Alexandra
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 may
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F iftene-balahur-dobrescu-2008-named
%X Discovering relations among Named Entities (NEs) from large corpora is both a challenging, as well as useful task in the domain of Natural Language Processing, with applications in Information Retrieval (IR), Summarization (SUM), Question Answering (QA) and Textual Entailment (TE). The work we present resulted from the attempt to solve practical issues we were confronted with while building systems for the tasks of Textual Entailment Recognition and Question Answering, respectively. The approach consists in applying grammar induced extraction patterns on a large corpus - Wikipedia - for the extraction of relations between a given Named Entity and other Named Entities. The results obtained are high in precision, determining a reliable and useful application of the built resource.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/192_paper.pdf
Markdown (Informal)
[Named Entity Relation Mining using Wikipedia](http://www.lrec-conf.org/proceedings/lrec2008/pdf/192_paper.pdf) (Iftene & Balahur-Dobrescu, LREC 2008)
ACL
- Adrian Iftene and Alexandra Balahur-Dobrescu. 2008. Named Entity Relation Mining using Wikipedia. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).