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Tagging French Without Lexical Probabilities - Combining Linguistic Knowledge And Statistical Learning
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Abstract:
This paper explores morpho-syntactic ambiguities for French to develop a strategy for part-of-speech disambiguation that a) reflects the complexity of French as an inflected language, b) optimizes the estimation of probabilities, c) allows the user flexibility in choosing a tagset. The problem in extracting lexical probabilities from a limited training corpus is that the statistical model may not necessarily represent the use of a particular word in a particular context. In a highly morphologically inflected language, this argument is particularly serious since a word can be tagged with a large number of parts of speech.
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Keyword:
Computer science; Information technology
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URL: https://doi.org/10.7916/D8S75QP4
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Tagging French Without Lexical Probabilities - Combining Linguistic Knowledge And Statistical Learning ...
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Tagging French Without Lexical Probabilities -- Combining Linguistic Knowledge And Statistical Learning ...
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