TY - GEN
T1 - Linguistic resources for entity linking evaluation
T2 - 8th International Conference on Language Resources and Evaluation, LREC 2012
AU - Li, Xuansong
AU - Strassel, Stephanie M.
AU - Ji, Heng
AU - Griffitt, Kira
AU - Ellis, Joe
N1 - Funding Information:
Heng Ji's work in this paper was supported by the U.S. Army Research Laboratory under Cooperative Agreement No. W911NF-09-2-0053 (NS-CTA), the U.S. NSF CAREER Award under Grant IIS-0953149, the U.S. NSF EAGER Award under Grant No. IIS-1144111, the U.S. DARPA Broad Operational Language Translations program and CUNY Junior Faculty Award. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.
PY - 2012
Y1 - 2012
N2 - To advance information extraction and question answering technologies toward a more realistic path, the U.S. NIST (National Institute of Standards and Technology) initiated the KBP (Knowledge Base Population) task as one of the TAC (Text Analysis Conference) evaluation tracks. It aims to encourage research in automatic information extraction of named entities from unstructured texts with the ultimate goal of integrating such information into a structured Knowledge Base. The KBP track consists of two types of evaluation: Named Entity Linking (NEL) and Slot Filling. This paper describes the linguistic resource creation efforts at the Linguistic Data Consortium (LDC) in support of Named Entity Linking evaluation of KBP, focusing on annotation methodologies, process, and features of corpora from 2009 to 2011, with a highlighted analysis of the cross-lingual NEL data. Progressing from monolingual to cross-lingual Entity Linking technologies, the 2011 cross-lingual NEL evaluation targeted multilingual capabilities. Annotation accuracy is presented in comparison with system performance, with promising results from cross-lingual entity linking systems.
AB - To advance information extraction and question answering technologies toward a more realistic path, the U.S. NIST (National Institute of Standards and Technology) initiated the KBP (Knowledge Base Population) task as one of the TAC (Text Analysis Conference) evaluation tracks. It aims to encourage research in automatic information extraction of named entities from unstructured texts with the ultimate goal of integrating such information into a structured Knowledge Base. The KBP track consists of two types of evaluation: Named Entity Linking (NEL) and Slot Filling. This paper describes the linguistic resource creation efforts at the Linguistic Data Consortium (LDC) in support of Named Entity Linking evaluation of KBP, focusing on annotation methodologies, process, and features of corpora from 2009 to 2011, with a highlighted analysis of the cross-lingual NEL data. Progressing from monolingual to cross-lingual Entity Linking technologies, the 2011 cross-lingual NEL evaluation targeted multilingual capabilities. Annotation accuracy is presented in comparison with system performance, with promising results from cross-lingual entity linking systems.
KW - Information extraction
KW - Knowledge Base
KW - Named entity linking
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M3 - Conference contribution
AN - SCOPUS:84959933342
T3 - Proceedings of the 8th International Conference on Language Resources and Evaluation, LREC 2012
SP - 3098
EP - 3105
BT - Proceedings of the 8th International Conference on Language Resources and Evaluation, LREC 2012
A2 - Dogan, Mehmet Ugur
A2 - Mariani, Joseph
A2 - Moreno, Asuncion
A2 - Goggi, Sara
A2 - Choukri, Khalid
A2 - Calzolari, Nicoletta
A2 - Odijk, Jan
A2 - Declerck, Thierry
A2 - Maegaard, Bente
A2 - Piperidis, Stelios
A2 - Mazo, Helene
A2 - Hamon, Olivier
PB - European Language Resources Association (ELRA)
Y2 - 21 May 2012 through 27 May 2012
ER -