Languages such as English contain a large number of words with multiple meanings. These words are commonly termed "lexlcal ambiguities", although it is probably more accurate to speak of them as potentially ambiguous. Determining how the contextually appropriate reading of a word is identified presents an important and unavoidable problem for persons developing theories of natural language proc...

Theodes of semantic interpretation which wish to capture as many generalizations as possible must face up to the manifoldly ambiguous and contextually dependent nature of word meaning? In this paper I present a two-level scheme of semantic interpretation in which the first level deals with the semantic consequences of'syntactic structure and the second with the choice of word meaning. On the fi...

Earlier research has suggested that left embedded words (e.g. cat in catalog) present a problem for spoken word recognition since it is potentially unclear whether there is a word boundary at the offset of cat. Models of spoken word recognition have incorporated processes of competition so that the identification of embedded words can be delayed until longer interpretations have been ruled out....

Lexical rules are used in constraintbased g rammar formalisms such as llead-Driven l)hrase Structure Gram m ar ( I IPSG) (Pollard and Sag 1994) to express generalizations atnong lexical entries. '['his paper discusses a number of lexical rules from recent I[PSG analyses of German (tlinri<;hs and Nakazawa 1994) and shows that the g r am m ar in some cases vastly overgenerates and in other cases ...

A grammar model for concurrent, object-oriented natural language parsing is introduced. Complete lexical distribution of grammatical knowledge is achieved building upon the head-oriented notions of valency and dependency, while inheritance mechanisms are used to capture lexical generalizations. The underlying concurrent computation model relies upon the actor paradigm. We consider message passi...

Language is rife with ambiguity. Do children and adults meet this challenge in similar ways? Recent work suggests that while adults resolve syntactic ambiguities by integrating a variety of cues, children are less sensitive to top-down evidence. We test whether this top-down insensitivity is specific to syntax or a general feature of children's linguistic ambiguity resolution by evaluating whet...

Over the last twenty years or so, the approaches to partof-speech tagging based on machine learning techniques have been developed or ported to provide high-accuracy morpho-lexical annotation for an increasing number of languages. Given the large number of morpho-lexical descriptors for a morphologically complex language, one has to consider ways to avoid the data sparseness threat in standard ...

This paper presents an approach to acquisition of some lexical and grammatical constraints from large corpora using genetic algorithms. The main aim is to use these constraints to automatically define local grammars that can be used to reduce lexical ambiguity usually found in an initially tagged text. A genetic algorithm for computation of the minimal representation of grammatical features of ...

The article describes a model of automatic analysis of puns, where a word is intentionally used in two meanings at the same time (the target word). We employ Roget’s Thesaurus to discover two groups of words, which, in a pun, form around two abstract bits of meaning (semes). They become a semantic vector, based on which an SVM classifier learns to recognize puns, reaching a score 0.73 for F-mea...

Lexical ambiguities naturally arise in languages. We present Lamb, a lexical analyzer that produces a lexical analysis graph describing all the possible sequences of tokens that can be found within the input string. Parsers can process such lexical analysis graphs and discard any sequence of tokens that does not produce a valid syntactic sentence, therefore performing, together with Lamb, a con...