Question answering over linked data has emerged in the past years as an important topic of research in order to provide natural language access to a growing body of linked open data on the Web. In this paper we focus on analyzing the lexical gap that arises as a challenge for any such question answering system. The lexical gap refers to the mismatch between the vocabulary used in a user questio...

We describe a compiler which translates a set of hpsg lexical rules and their interaction into deenite relations used to constrain lexical entries. The compiler ensures automatic transfer of properties unchanged by a lexical rule. Thus an operational semantics for the full lexical rule mechanism as used in HPSG linguistics is provided. Program transformation techniques are used to advance the r...

We describe a compiler which translates a set of hpsg lexical rules and their interaction into deenite relations used to constrain lexical entries. The compiler ensures automatic transfer of properties unchanged by a lexical rule. Thus an operational semantics for the full lexical rule mechanism as used in HPSG linguistics is provided. Program transformation techniques are used to advance the r...

The coverage of a parser depends mostly on the quality of the underlying grammar and lexicon. The development of a lexicon both complete and accurate is an intricate and demanding task. We introduce a automatic process for detecting missing, incomplete and erroneous entries in a morphological and syntactic lexicon, and for suggesting corrections hypotheses for these entries. The detection of du...

Text processing technologies require increasing amounts of information about words and phrases to cope with the massive amounts of textual material available today. Information retrieval search engines provide greater and greater coverage, but do not provide a capability for identifying the specific content that is sought. Greater reliance is placed on natural language processing (NLP) technolo...

We present a framework for learning a pronunciation lexicon for an Automatic Speech Recognition (ASR) system from multiple utterances of the same training words, where the lexical identities of the words are unknown. Instead of only trying to learn pronunciations for known words we go one step further and try to learn both spelling and pronunciation in a joint optimization. Decoding based on li...

Spoken word recognition models treat mismatching sensory information differently. Mismatching information deactivates lexical entries according to one type of models. In another type of models, lexical entries are activated reflecting their degree of match with the input. This issue is mainly investigated with cross-modal semantic priming and lexical decision. This paradigm has been suspected o...

Disambiguation of heterophonic and homophonic homographs was investigated in Hebrew using semantic priming. Ambiguous primes were followed by unambiguous targets at 100 ms, 250 ms, and 750 ms stimulus onset asynchrony (SOA). Lexical decision for targets related to the dominant phonological alternatives of heterophonic homographs were facilitated at all SOAs. Targets related to subordinate alter...

This paper is a contribution to the issue – which has, in the course of the last decade, become critical – of the basic requirements and validation criteria for lexical language resources in Standard Arabic. The work is based on a critical analysis of the architecture of the DIINAR.1 lexical database, the entries of which are associated with grammar-lexis relations operating at word-form level ...

SMOOTHING A PROBABILISTIC LEXICON VIA SYNTACTIC TRANSFORMATIONS Jason Michael Eisner Supervisor: Professor Mitch Marcus Probabilistic parsing requires a lexicon that specifies each word’s syntactic preferences in terms of probabilities. To estimate these probabilities for words that were poorly observed during training, this thesis assumes the existence of arbitrarily powerful transformations (...