[PDF] Top 20 Don’t Blame Distributional Semantics if it can’t do Entailment

... formal semantics pro- claims, yet the second is what formal semantics does, given that the notions it composes in fact reside at the level of speaker meaning ...to T HE W ORD C AT ; and the end ... See full document

... relevant entailment phe- nomena, though each individually may be rele- vant to relatively few RTE examples (the Sparse- ness problem), we know of no systematic analysis to determine what those phenomena are, and ... See full document

... lexical entailment that reaches state-of-the- art performance with little or no manual interven- ...Lexical entailment is in turn fundamental for constructing ontologies and other lexical re- sources ... See full document

... lexical entailment information to NLP appli- cations (Bos and Markert, ...using distributional semantics (Weeds and Weir, 2003; Weeds et ...the distributional vectors A ~ and ...frequency ... See full document

... This paper suggests refinements for the Distributional Similarity Hypothesis. Our proposed hypotheses relate the distribu- tional behavior of pairs of words to lexical entailment – a tighter notion of ... See full document

... the semantics of phrases or sentences (Mitchell and Lapata, ...that can recognise entailments such as all dogs = ⇒ some dogs, but this remains some way from the power of first-order theorem proving of the ... See full document

... a distributional semantics space to some heavily underspecified form of a “model-theoretic” space (Herbelot and Vecchi 2015); (c) a function from sentences in a discourse to other sentences in the same ... See full document

... textual entailment have more in common than meets the ...Markert can be understood in terms of the logic programming methodology advocated by Baral et ...textual entailment problems used to test the ... See full document

... Semantic specialization methods fine-tune dis- tributional word vectors using lexical knowl- edge from external resources (e.g., WordNet) to accentuate a particular relation between words. However, such post-processing ... See full document

... Montague semantics. However, their version of Montague semantics assumed a particular model, and thus effectively mapped sentences to truth ...Montague semantics in which sentences are mapped to ... See full document

... sages is one of the most useful features that the computational analysis of text could provide (Dagan et al., 2009). I test the model on the SICK entailment task (sick-e) (Marelli et al., 2014). All SICK sentence ... See full document

... Besides using MRS, one novel aspect of this work is an investigation of using n-best lists of parser outputs in deciding on entailment relations. In principle, the top-ranked (i.e., most probable) parser output ... See full document

... compositional distributional semantics, as well as making the relevant techniques easily available to those interested in their many potential applica- tions, ...textual entailment or paraphrase ... See full document

... unknown. Entailment between these dis- crete binary vectors can be calculated by indepen- dently checking each ...to do calculations with distributions over these vectors, we need to deal with the ... See full document

... features do better than SIFT ...We can thus confirm that, by limiting multimodal spaces to SIFT features, as has been done until now in the lit- erature, we are missing important semantic informa- tion, ... See full document

... Let us reconsider the highly underspecified definition of the Principle of Compositionality. Let us start by setting the syntactic relation that we want to focus on for the purposes of this study: following Guevara ... See full document

... We present a set of general methods for smooth- ing vector similarity computations given a resource that groups words into derivational families (equiv- alence classes) and evaluate these methods on Ger- man for two ... See full document

... a distributional model takes the form of a sparse matrix, with entries specified as a triplet of row label (target term), column label (feature term) and co-occurrence frequency ...which can easily be ... See full document

... types can be seen as representing a cline in transparency, with intersective types the most transparent and intensional types the most relatively ...a distributional model of AB semantic transparency, the ... See full document

... our distributional semantic model construc- tion, the important point to keep in mind is that stan- dard parameter choices such as the ones we adopted lead to distributional vectors with 4K, 8K, ... See full document