Nbest Dependency Parsing with linguistically rich models
نویسنده
چکیده
We try to improve the classifier-based deterministic dependency parsing in two ways: by introducing a better search method based on a non-deterministic nbest algorithm and by devising a series of linguistically richer models. It is experimentally shown on a ConLL 2007 shared task that this results in a system with higher performance while still keeping it simple enough for an efficient implementation.
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تاریخ انتشار 2007