[PDF] Top 20 Unsupervised Grammar Induction by Distribution and Attachment

... Distributional approaches to grammar induction fall into two categories, depending on their treat- ment of nested structure. The first category cov- ers Expectation-Maximization (EM) systems. These systems ... See full document

... The attachment accuracy for this set of experi- ments is described in Table ...right attachment (where each word is attached to the word to its right), MLE via EM (Klein and Man- ning, 2004), and empirical ... See full document

... a grammar induction sytem that models the working memory limitations of young language learners and employs a cognitively plausible left-corner incremental parsing strategy, in contrast to existing raw-text ... See full document

... 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. ... See full document

... categorial grammar (Steedman, 2000) are amenable to more stringent evaluation metrics, which enable detailed analyses of the construc- tions they capture, while the commonly used unlabeled directed ... See full document

... A strong inductive bias is essential in un- supervised grammar induction. We ex- plore a particular sparsity bias in de- pendency grammars that encourages a small number of unique dependency types. ... See full document

... to unsupervised GI exploit the principle of substitutability: con- stituents of the same type may be exchanged with one another without affecting the syntax of the surrounding ...to grammar induction ... See full document

... Sch¨utze (1995) presents a series of part-of-speech inducers based on distributional clustering. We implement the baseline system, which Klein and Manning (2002) use for their grammar induction experiments ... See full document

... [the/ DT tree/ NN ]]], the sequence VB DT NN is gen- erated as a constituent yield, since it constitutes a complete bracket in the tree. On the other hand, the sequence VB DT is generated as a distituent, since it does ... See full document

... dependency grammar induction, unsuper- vised methods achieve continuous improvements in recent years (Klein and Manning, 2004; Smith and Eisner, 2005; Bod, 2006; William et ...an unsupervised model ... See full document

... ing from raw text, and it is also incremental and ex- tremely fast for both learning and parsing. Unfortu- nately, CCL is a non-probabilistic algorithm based on a complex set of inter-relating heuristics and a ... See full document

... Dyer and Resnik (2010) treat reordering as a la- tent variable and try to sum over all derivations that lead not only to the same reordering but also to the same translation. In their work they consider all permutations ... See full document

... The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study[r] ... See full document

... of unsupervised bracketing on which much progress has been made in recent years (Klein and Manning, 2002b; Bod, ...Together, unsupervised bracketing and unsupervised labeling hold the promise of (i) ... See full document

... In unsupervised grammar induction, data like- lihood is known to be only weakly cor- related with parsing accuracy, especially at convergence after multiple ...multilingual grammar ... See full document

... attachment probability for English. However, be- cause that feature does not show up in any other language, it is not usefully controlled by the prior. Therefore, we also include coarser features which activate on ... See full document

... Heuristic Extraction of Unambiguous Cases Given a tagged and chunked sentence, the extraction heuristic returns head word tuples of the form v,p, n2 or n,p, n2, where v is the verb, n is[r] ... See full document

... Statistical Models for Unsupervised Prepositional Phrase Attachment S t a t i s t i c a l M o d e l s for U n s u p e r v i s e d P r e p o s i t i o n a l P h r a s e A t t a c h m e n t A d w a i t[.] ... See full document

... an unsupervised algorithm for argument identifica- tion that relies only on part-of-speech annotations, whereas Grenager and Manning (2006) focus on role induction which they formalize as probabilis- tic ... See full document

... artificial grammar learning study, Lai & Poletiek (2011) found that human participants could learn a center-embedded recursive grammar only if the input during training was presented in a staged ... See full document