Resume This paper evaluates the impact of external lexical resources into a CRF-based joint Multiword Segmenter and Part-of-Speech Tagger. We especially show different ways of integrating lexicon-based features in the tagging model. We display an absolute gain of 0.5% in terms of f-measure. Moreover, we show that the integration of lexicon-based features significantly compensates the u se of a small training corpus.
['Matthieu Constant', 'Isabelle Tellier']
Evaluating the Impact of External Lexical Resources into a CRF-based Multiword Segmenter and Part-of-Speech Tagger