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We formulate dependency parsing as a graphical model with the novel ingredient of global constraints. We show how to apply loopy belief propagation (BP), a simple and effective tool for …...

In this paper, we first demonstrate the in- terest of the Loopy Belief Propagation al- gorithm to train and use a simple align- ment model where the expected marginal values …...

We present our entries for the SemEval- 2013 cross-language word-sense disambigua- tion task (Lefever and Hoste, 2013). We submitted three systems based on classifiers trained on local context features, with …...

We introduce ConnotationWordNet, a con- notation lexicon over the network of words in conjunction with senses. We formulate the lexicon induction problem as collec- tive inference over pairwise-Markov Ran- dom …...

Opinions may be expressed implicitly via inference over explicit sentiments and events that positively/negatively affect en- tities (goodFor/badFor events). We in- vestigate how such inferences may be exploited to improve …...

We present a structured learning approach to inducing hypernym taxonomies using a probabilistic graphical model formulation. Our model incorporates heterogeneous re- lational evidence about both hypernymy and siblinghood, captured by …...

We investigate dual decomposition for joint MAP inference of many strings. Given an arbitrary graphical model, we de- compose it into small acyclic sub-models, whose MAP configurations can be found …...

This paper addresses the problem of comment classification in community Question Answer- ing. Following the state of the art, we ap- proach the task with a global inference pro- cess …...

AbstractWe present the Berkeley Crossword Solver, a state-of-the-art approach for automatically solving crossword puzzles. Our system works by generating answer candidates for each crossword clue using neural question answering models …...