We propose the use of multilingual corpora in the automatic classification of verbs. We extend the work of (Merlo and Stevenson, 2001), in which statistics over simple syntactic features extracted from textual corpora were used to train an automatic classifier for three lexical semantic classes of English verbs. We hypothesize that some lexical semantic features that are di#cult to detect superficially in English may manifest themselves as easily extractable surface syntactic features in another language. Our experimental results combining English and Chinese features show that a small bilingual corpus may provide a useful alternative to using a large monolingual corpus for verb classification
VerbNet-the most extensive online verb lexicon currently available for English-has proved useful in ...
A common practice in operational Machine Translation (MT) and Natural Language Processing (NLP) syst...
We address the problem of identifying mul-tiword expressions in a language, focus-ing on English phr...
grantor: University of TorontoLexical semantic classes incorporate both syntactic and sema...
We develop a general feature space that can be used for the semantic classification of English verbs...
Automatically acquiring semantic verb classes from corpora is a challenging task, especially with no...
We apply machine learning techniques to classify automatically a set of verbs into lexical semanti...
Abstract. Lexical classifications have proved useful in supporting various natural language processi...
In this paper, we present the first analysis of bottom-up manual semantic clustering of verbs in thr...
Advances in representation learning have enabled natural language processing models to derive non-ne...
Lexical semantic classes of verbs play an important role in structuring complex predicate informatio...
The goal of the diploma thesis is to design, implement and evaluate classifiers for automatic classi...
We give a report on a detailed study of automatic lexical disambiguation of 30 sample English verbs....
In this report, we investigate the relationship between the semantic and syntactic properties of ver...
We present the first evaluation of the applicability of a spatial arrangement method (SpAM) to a typ...
VerbNet-the most extensive online verb lexicon currently available for English-has proved useful in ...
A common practice in operational Machine Translation (MT) and Natural Language Processing (NLP) syst...
We address the problem of identifying mul-tiword expressions in a language, focus-ing on English phr...
grantor: University of TorontoLexical semantic classes incorporate both syntactic and sema...
We develop a general feature space that can be used for the semantic classification of English verbs...
Automatically acquiring semantic verb classes from corpora is a challenging task, especially with no...
We apply machine learning techniques to classify automatically a set of verbs into lexical semanti...
Abstract. Lexical classifications have proved useful in supporting various natural language processi...
In this paper, we present the first analysis of bottom-up manual semantic clustering of verbs in thr...
Advances in representation learning have enabled natural language processing models to derive non-ne...
Lexical semantic classes of verbs play an important role in structuring complex predicate informatio...
The goal of the diploma thesis is to design, implement and evaluate classifiers for automatic classi...
We give a report on a detailed study of automatic lexical disambiguation of 30 sample English verbs....
In this report, we investigate the relationship between the semantic and syntactic properties of ver...
We present the first evaluation of the applicability of a spatial arrangement method (SpAM) to a typ...
VerbNet-the most extensive online verb lexicon currently available for English-has proved useful in ...
A common practice in operational Machine Translation (MT) and Natural Language Processing (NLP) syst...
We address the problem of identifying mul-tiword expressions in a language, focus-ing on English phr...