Summary of the paper
| Title | Named Entity Relation Mining using Wikipedia |
|---|---|
| Authors | Adrian Iftene and Alexandra Balahur-Dobrescu |
| 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. |
| Language | Multiple languages |
| Topics | Information Extraction, Information Retrieval, Grammars, Text mining |
Full paper |
Named Entity Relation Mining using Wikipedia |
Slides |
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| Bibtex | @InProceedings{IFTENE08.192, author = {Adrian Iftene and Alexandra Balahur-Dobrescu}, title = {Named Entity Relation Mining using Wikipedia}, booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)}, year = {2008}, month = {may}, date = {28-30}, address = {Marrakech, Morocco}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-4-0}, note = {http://www.lrec-conf.org/proceedings/lrec2008/}, language = {english} } |