Paper: Transfer Learning for Constituency-Based Grammars

ACL ID P13-1029
Title Transfer Learning for Constituency-Based Grammars
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013

In this paper, we consider the problem of cross-formalism transfer in parsing. We are interested in parsing constituency- based grammars such as HPSG and CCG using a small amount of data specific for the target formalism, and a large quan- tity of coarse CFG annotations from the Penn Treebank. While all of the target formalisms share a similar basic syntactic structure with Penn Treebank CFG, they also encode additional constraints and se- mantic features. To handle this appar- ent discrepancy, we design a probabilistic model that jointly generates CFG and tar- get formalism parses. The model includes features of both parses, allowing trans- fer between the formalisms, while pre- serving parsing efficiency. We evaluate our approach on three constituency-based grammars ? CCG, HPSG, and LFG,...