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Our system for the SENSEVAL-2 all words task uses automatically acquired selectional prefer- ences to sense tag subject and object head nouns, along with the associated verbal pred- icates. The …...

Previous work on the induction of se- lectional preferences has been mainly carried out for English and has concen- trated almost exclusively on verbs and their direct objects. In this …...

We propose a new, simple model for the auto- matic induction of selectional preferences, using corpus-based semantic similarity metrics. Fo- cusing on the task of semantic role labeling, we compute …...

In this paper we explore the use of se- lectional preferences for detecting non- compositional verb-object combinations. To characterise the arguments in a given gram- matical relationship we experiment with …...

This paper presents an innovative, complex approach to semantic verb classification that relies on selectional preferences as verb prop- erties. The probabilistic verb class model un- derlying the semantic classes …...

The validity of semantic inferences depends on the contexts in which they are applied. We propose a generic framework for handling contextual considerations within applied in- ference, termed Contextual Preferences. …...

We conduct large-scale experiments to in- vestigate optimal features for classification of verbs in biomedical texts. We intro- duce a range of feature sets and associated extraction techniques, and evaluate …...

The computation of selectional prefer- ences, the admissible argument values for a relation, is a well-known NLP task with broad applicability. We present LDA-SP, which utilizes LinkLDA (Erosheva et al., …...

We present a novel approach to metaphor in- terpretation and a system that produces lit- eral paraphrases for metaphorical expressions. Such a representation is directly transferable to other applications that …...

AbstractThis paper presents a comparison of three computational approaches to selectional preferences: (i) an intuitive distributional approach that uses second-order co-occurrence of predicates and complement properties; (ii) an EM-based clustering …...

This work incorporates Selectional Prefer- ences (SP) into a Semantic Role (SR) Clas- sification system. We learn separate selec- tional preferences for noun phrases and prepo- sitional phrases and we …...

This paper improves the use of pseudo- words as an evaluation framework for selectional preferences. While pseudo- words originally evaluated word sense disambiguation, they are now commonly used to evaluate …...

In this paper, we present a novel approach which incorporates the web-derived selec- tional preferences to improve statistical de- pendency parsing. Conventional selectional preference learning methods have usually fo- cused …...

AbstractThis paper describes the derivation of distributional semantic representations for open class words relative to a concept inventory, and of concepts relative to open class words through grammatical relations extracted …...

LDA-frames is an unsupervised approach for identifying semantic frames from semanti- cally unlabeled text corpora, and seems to be a useful competitor for manually created databases of selectional preferences. The …...

This paper investigates the use of neural networks for the acquisition of selectional preferences. Inspired by recent advances of neural network models for NLP applica- tions, we propose a neural …...

AbstractTranslating prepositions is a difficult and under-studied problem in SMT. We present a novel method to improve the translation of prepositions by using noun classes to model their selectional preferences. …...

AbstractThis article presents the semantic layer of Walenty―a new valence dictionary of Polish predicates, with a number of novel features, as compared to other such dictionaries. The dictionary contains two …...

AbstractCreating annotated frame lexicons such as PropBank and FrameNet is expensive and labor intensive. We present a method to induce an embedded frame lexicon in an minimally supervised fashion using …...

AbstractSelectional preferences have long been claimed to be essential for coreference resolution. However, they are modeled only implicitly by current coreference resolvers. We propose a dependency-based embedding model of selectional …...

AbstractOur paper offers a computational model of the semantic recoverability of verb arguments, tested in particular on direct objects and Instruments. Our fully distributional model is intended to improve on …...