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Evaluation of Dependency Parsers on Unbounded Dependencies

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If you have a question about this talk, please contact Laura Rimell.

Joint work with Joakim Nivre, Ryan McDonald and Carlos Gómez-Rodríguez.

We evaluate two dependency parsers, MST Parser and MaltParser, with respect to their capacity to recover unbounded dependencies in English, a type of evaluation that has been applied to grammar-based parsers and statistical phrase structure parsers but not to dependency parsers. The evaluation shows that when combined with simple post-processing heuristics, the parsers correctly recall unbounded dependencies roughly 50% of the time, which is only slightly worse than two grammar-based parsers specifically designed to cope with such dependencies.

This talk is part of the NLIP Seminar Series series.

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