Identifying Sources of Weakness in Syntactic Lexicon Extraction

Previous work has shown that large scale subcategorisation lexicons could be extracted from parsed corpora with reasonably high precision. In this paper, we apply a standard extraction procedure to a 100 millions words parsed corpus of French and obtain rather poor results. We investigate different factors likely to improve performance such as in particular, the specific extraction procedure and the parser used; the size of the input corpus; and the type of frames learned. We try out different ways of interleaving the output of several parsers with the lexicon extraction process and show that none of them improves the results. Conversely, we show that increasing the size of the input corpus and modifying the extraction procedure to better differentiate prepositional arguments from prepositional modifiers improves performance. In conclusion, we suggest that a more sophisticated approach to parser combination and better probabilistic models of the various types of prepositional objects in French are likely ways to yield better results.