摘要：We compare three different approaches to parsing into syntactic,bilexical dependencies for English: a ‘direct’ data-driven dependency parser,a statistical phrase structure parser,and a hybrid,‘deep’ grammar-driven parser.The analyses from the latter two are post_converted to bi-lexical dependencies.Through this ‘reduction’ of all three approaches to syntactic dependency parsers,we determine em_pirically what performance can be obtained for a common set of de?pendency types for English;in- and out-of-domain experimentation ranges over diverse text types.In doing so,we observe what trade-offs apply along three dimensions: accuracy,efficiency,and resilience to domain variation.Our results suggest that the hand-built grammar in one of our parsers helps in both accuracy and cross-domain parsing performance.When evaluated extrinsically in two downstream tasks – negation resolution and semantic dependency parsing – these ac?curacy gains do sometimes but not always translate into improved end-to-end performance.
