674 research outputs found
Latent-Variable PCFGs: Background and Applications
Latent-variable probabilistic context-free grammars are
latent-variable models that are based on context-free grammars.
Nonterminals are associated with latent states that provide
contextual information during the top-down rewriting process of
the grammar.
We survey a few of the techniques used to estimate such grammars
and to parse text with them. We also give an overview of what the latent
states represent for English Penn treebank parsing, and provide
an overview of extensions and related models to these grammars
Elimination of Spurious Ambiguity in Transition-Based Dependency Parsing
We present a novel technique to remove spurious ambiguity from transition
systems for dependency parsing. Our technique chooses a canonical sequence of
transition operations (computation) for a given dependency tree. Our technique
can be applied to a large class of bottom-up transition systems, including for
instance Nivre (2004) and Attardi (2006)
Unsupervised Bilingual POS Tagging with Markov Random Fields
In this paper, we give a treatment to the problem of bilingual part-of-speech induction with parallel data. We demonstrate that naïve optimization of log-likelihood with joint MRFs suffers from a severe problem of local maxima, and suggest an alternative – using contrastive estimation for estimation of the parameters. Our experiments show that estimating the parameters this way, using overlapping features with joint MRFs performs better than previous work on the 1984 dataset.
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