Less is More, More or Less... Finding the Optimal Threshold for Lexicalization in Chunking
Abstract: Lexicalization of the input of sequential taggers has gone a long way since it was invented by Molina and Pla [4]. In this paper we thoroughly investigate the method introduced by Indig and Endrédy [2] to find out the best lexicalization level for chunking and to explore the behavior of different IOB representations. Both tasks are applied to the CoNLL-2000 dataset. Our goal is to introduce a transformation method to accommodate the parameters of the development set to the training set using their frequency distributions which other tasks like POS tagging or NER could benefit too.
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| Format: | Digital revista |
| Language: | English |
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Instituto Politécnico Nacional, Centro de Investigación en Computación
2017
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| Online Access: | http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1405-55462017000400637 |
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