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Date: 2013
Language: eng
Resource Type: journal article
Identifier: http://hdl.handle.net/1959.14/221384
Description: Named Entity Linking (nel) grounds entity mentions to their corresponding node in a Knowledge Base (kb). Recently, a number of systems have been proposed for linking entity mentions in text to Wikiped... More
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Date: 2012
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/216193
Description: Interpreting news requires identifying its constituent events. Events are complex linguistically and ontologically, so disambiguating their reference is challenging. We introduce event linking, which ... More
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Date: 2011
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/154190
Description: Named entity linking (NEL) grounds entity mentions to their corresponding Wikipedia article. State-of-the-art supervised NEL systems use features over the rich Wikipedia document and link-graph struct... More
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Authors: Hachey, Ben
Date: 2006
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/156253
Description: We present results on the relation discovery task, which addresses some of the shortcomings of supervised relation extraction by applying minimally supervised methods. We describe a detailed experimen... More
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Date: 2006
Language: eng
Resource Type: journal article
Identifier: http://hdl.handle.net/1959.14/146720
Description: We describe research carried out as part of a text summarisation project for the legal domain for which we use a new XML corpus of judgments of the UK House of Lords. These judgments represent a parti... More
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Date: 2005
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/155811
Description: We report on an active learning experiment for named entity recognition in the astronomy domain. Active learning has been shown to reduce the amount of labelled data required to train a supervised lea... More
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Date: 2005
Subject Keyword: 080400 Data Format
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/149773
Description: We describe a set of experiments using a wide range of machine learning techniques for the task of predicting the rhetorical status of sentences. The research is part of a text summarisation project f... More
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