Paper: Prototype-Driven Grammar Induction

ACL ID P06-1111
Title Prototype-Driven Grammar Induction
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006

We investigate prototype-driven learning for pri- marily unsupervised grammar induction. Prior knowledge is specified declaratively, by providing a few canonical examples of each target phrase type. This sparse prototype information is then propa- gated across a corpus using distributional similar- ity features, which augment an otherwise standard PCFG model. We show that distributional features areeffectiveatdistinguishingbracketlabels, butnot determiningbracketlocations. Toimprovethequal- ity of the induced trees, we combine our PCFG in- duction with the CCM model of Klein and Manning (2002), which has complementary stengths: it iden- tifies brackets but does not label them. Using only a handful of prototypes, we show substantial im- provements over naive PCFG induction for English and C...