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ACL
2001

Using Machine Learning to Maintain Rule-based Named-Entity Recognition and Classification Systems

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Using Machine Learning to Maintain Rule-based Named-Entity Recognition and Classification Systems
This paper presents a method that assists in maintaining a rule-based named-entity recognition and classification system. The underlying idea is to use a separate system, constructed with the use of machine learning, to monitor the performance of the rule-based system. The training data for the second system is generated with the use of the rule-based system, thus avoiding the need for manual tagging. The disagreement of the two systems acts as a signal for updating the rule-based system. The generality of the approach is illustrated by applying it to large corpora in two different languages: Greek and French. The results are very encouraging, showing that this alternative use of machine learning can assist significantly in the maintenance of rulebased systems.
Georgios Petasis, Frantz Vichot, Francis Wolinski,
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where ACL
Authors Georgios Petasis, Frantz Vichot, Francis Wolinski, Georgios Paliouras, Vangelis Karkaletsis, Constantine D. Spyropoulos
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