Projects per year
Incremental parsers have potential advantages for applications like language modeling for machine translation and speech recognition. We describe a new algorithm for incremental transition-based Combinatory Categorial Grammar parsing. As English CCGbank derivations are mostly right branching and non-incremental, we design our algorithm based on the dependencies resolved rather than the derivation. We introduce two new actions in the shift-reduce paradigm based on the idea of ‘revealing’ (Pareschi and Steedman, 1987) the required information during parsing. On the standard CCGbank test data, our algorithm achieved improvements of 0.88% in labeled and 2.0% in unlabeled F-score over a greedy non-incremental shift-reduce parser.
|Title of host publication||Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies|
|Place of Publication||Denver, Colorado|
|Publisher||Association for Computational Linguistics|
|Number of pages||11|
|Publication status||Published - 1 May 2015|
Steedman, M., Geib, C. & Petrick, R.
1/01/10 → 31/12/15