This has two main benefits: (i) Definitional sentences express (sense-specific) corpus-independent meanings of words, hence definition-driven approaches enable strong generalization-once trained, the model is expected to work well in opendomain testbeds; (ii) Global context from a large corpus and definitions provide complementary information for words.
our model, HYPERDEF, once trained on taskagnostic data, gets state-of-the-art results in multiple benchmarks 1 .