The GREC named entity generation challenge 2009; Overview and evaluation results

Anja Belz; Eric Kow; Jette Viethen

The GREC named entity generation challenge 2009; Overview and evaluation results

Anja Belz, Eric Kow, Jette Viethen

University of Brighton

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

Abstract

The GREC-NEG Task at Generation Challenges 2009 required participating systems to select coreference chains for all people entities mentioned in short encyclopaedic texts about people collected from Wikipedia. Three teams submitted six systems in total, and we additionally created four baseline systems. Systems were tested automatically using a range of existing intrinsic metrics. We also evaluated systems extrinsically by applying coreference resolution tools to the outputs and measuring the success of the tools. In addition, systems were tested in an intrinsic evaluation involving human judges. This report describes the GREC-NEG Task and the evaluation methods applied, gives brief descriptions of the participating systems, and presents the evaluation results.

Original language	English
Title of host publication	2009 Workshop on Language Generation and Summarisation
Pages	88-98
Number of pages	11
Publication status	Published - 2009
Event	2009 Workshop on Language Generation and Summarisation - Suntec, Singapore Duration: 1 Jan 2009 → …

Workshop

Workshop	2009 Workshop on Language Generation and Summarisation
Period	1/01/09 → …

Access to Document

http://aclweb.org/anthology-new/W/W09/W09-2817.pdfLicence: Unspecified

Cite this

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title = "The GREC named entity generation challenge 2009; Overview and evaluation results",

abstract = "The GREC-NEG Task at Generation Challenges 2009 required participating systems to select coreference chains for all people entities mentioned in short encyclopaedic texts about people collected from Wikipedia. Three teams submitted six systems in total, and we additionally created four baseline systems. Systems were tested automatically using a range of existing intrinsic metrics. We also evaluated systems extrinsically by applying coreference resolution tools to the outputs and measuring the success of the tools. In addition, systems were tested in an intrinsic evaluation involving human judges. This report describes the GREC-NEG Task and the evaluation methods applied, gives brief descriptions of the participating systems, and presents the evaluation results.",

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AB - The GREC-NEG Task at Generation Challenges 2009 required participating systems to select coreference chains for all people entities mentioned in short encyclopaedic texts about people collected from Wikipedia. Three teams submitted six systems in total, and we additionally created four baseline systems. Systems were tested automatically using a range of existing intrinsic metrics. We also evaluated systems extrinsically by applying coreference resolution tools to the outputs and measuring the success of the tools. In addition, systems were tested in an intrinsic evaluation involving human judges. This report describes the GREC-NEG Task and the evaluation methods applied, gives brief descriptions of the participating systems, and presents the evaluation results.

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