IWCS

This paper presents an update semantic for dialogue acts, defined in terms of combinations of very simple 'elementary update functions'. This approach allows fine-grained distinctions to be made between related types of dialogue acts, and relations like ...

Despite hundreds of years of study on semantics, theories and representations of semantic content---the actual meaning of the symbols used in semantic propositions---remain impoverished. The traditional extensional and intensional models of semantics ...

We present a method for training a statistical model for mapping natural language sentences to semantic expressions. The semantics are expressions of an underspecified logical form that has properties making it particularly suitable for statistical ...

This paper explores the role played by a multilingual feature representation for the task of word sense disambiguation. We translate the context of an ambiguous word in multiple languages, and show through experiments on standard datasets that by using ...

We present a system to translate natural language sentences to formulas in a formal or a knowledge representation language. Our system uses two inverse λ-calculus operators and using them can take as input the semantic representation of some words, ...

This paper presents a model to compose semantic relations. The model is independent of any particular set of relations and uses an extended definition for semantic relations. This extended definition includes restrictions on the domain and range of ...

Abduction is a method for finding the best explanation for observations. Arguably the most advanced approach to abduction, especially for natural language processing, is weighted abduction, which uses logical formulas with costs to guide inference. But ...

Taking an asynchronous perspective on the syntax-semantics interface, we propose to use modular graph rewriting systems as the model of computation. We formally define them and demonstrate their use with a set of modules which produce underspecified ...

In three experiments, we investigated the computational complexity of German reciprocal sentences with different quantificational antecedents. Building upon the tractable cognition thesis (van Rooij, 2008) and its application to the verification of ...

The VerbNet lexical resource classifies English verbs based on semantic and syntactic regularities and has been used for numerous NLP tasks, most notably, semantic role labeling. Since, in addition to thematic roles, it also provides semantic predicates,...

Entailment pairs are sentence pairs of a premise and a hypothesis, where the premise textually entails the hypothesis. Such sentence pairs are important for the development of Textual Entailment systems. In this paper, we take a closer look at a ...

First-order logic provides a powerful and flexible mechanism for representing natural language semantics. However, it is an open question of how best to integrate it with uncertain, probabilistic knowledge, for example regarding word meaning. This paper ...

This paper presents a novel approach to semantic role annotation implementing an entailment-based view of the concept of semantic role. I propose to represent arguments of predicates with grammatically relevant primitive properties entailed by the ...

Coecke, Sadrzadeh, and Clark [3] developed a compositional model of meaning for distributional semantics, in which each word in a sentence has a meaning vector and the distributional meaning of the sentence is a function of the tensor products of the ...

This article introduces and evaluates an approach to semantic compositionality in computational linguistics based on the combination of Distributional Semantics and supervised Machine Learning. In brief, distributional semantic spaces containing ...

We present the first approach to learning the durations of events without annotated training data, employing web query patterns to infer duration distributions. For example, we learn that "war" lasts years or decades, while "look" lasts seconds or ...

This paper proposes a framework for representing cross-lingual/interlingual lexical semantic correspondences that are expected to be recovered through a series of on-demand/on-the-fly invocations of a lexical semantic matching process. One of the ...

This paper argues that all subject noun phrases can be given a quantified formalisation in terms of the intersection between their denotation set and the denotation set of their verbal predicate. The majority of subject noun phrases, however, are only ...

We present the results of several machine learning tasks that exploit explicit spatial language to classify rhetorical relations and the spatial information of narrative events. Three corpora are annotated with figure and ground (granularity) ...

Measures of similarity have traditionally focused on computing the semantic relatedness between pairs of words and texts. In this paper, we construct an evaluation framework to quantify cross-modal semantic relationships that exist between arbitrary ...

We describe the methodology for constructing axioms defining event-related words, anchored in core theories of change of state and causality. We first derive from WordNet senses a smaller set of abstract, general "supersenses". We encode axioms for ...

We propose a method to automatically align WordNet synsets and Wikipedia articles to obtain a sense inventory of higher coverage and quality. For each WordNet synset, we first extract a set of Wikipedia articles as alignment candidates; in a second step,...

In the Recognizing Textual Entailment (RTE) task, sentence pairs are classified into one of three semantic relations: Entailment, Contradiction or Unknown. While we find some sentence pairs hold full entailments or contradictions, there are a number of ...

This paper presents a discourse processing framework based on weighted abduction. We elaborate on ideas described in Hobbs et al. (1993) and implement the abductive inference procedure in a system called Mini-TACITUS. Particular attention is paid to ...

This paper presents a machine learning-based approach to the incremental understanding of dialogue utterances, with a focus on the recognition of their communicative functions. A token-based approach combining the use of local classifiers, which exploit ...

We use data from a virtual world game for automated learning of words and grammatical constructions and their meanings. The language data are an integral part of the social interaction in the game and consist of chat dialogue, which is only constrained ...

Before starting, I would like to ask reader's opinion about the truth/falsity of certain NL statements. The statements are about figures depicting dots connected to stars. In the figures, we distinguish between dots and stars that are connected, i.e. ...

We consider the problem of distinguishing polysemous from homonymous nouns. This distinction is often taken for granted, but is seldom operationalized in the shape of an empirical model. We present a first step towards such a model, based on WordNet ...

WordNet is extensively used as a major lexical resource in NLP. However, its quality is far from perfect, and this alters the results of applications using it. We propose here to complement previous efforts for "cleaning up" the top-level of its ...

The past year has witnessed a surge of interest in the issue of compositional semantics: modelling the meaning of complex phrases. To date, distributional approaches have successfully dealt only with the meaning of individual words in context. Recent ...