For SENSEVAL-2, we disambiguated the lexical sample using two different sense inventories. Official SENSEVAL-2 results were generated using WordNet, and separately using the New Oxford Dictionary of English (NODE). Since our initial submission, we have implemented additional routines and have now examined the differences in the features used for making sense selections. We report here the contribution of default sense selection, idiomatic usage, syntactic and semantic clues, subcategorization patterns, word forms, syntactic usage, context, selectional preferences, and topics or subject fields. We also compare the differences between WordNet and NODE. Finally, we compare these features to those identified as significant in supervised learnin...
In this paper, we evaluate the results of the Antwerp University word sense disambiguation system in...
Domains are common areas of human discussion, such as economics, politics, law, science, etc., which...
There has been a tradition of combining differ-ent knowledge sources in Artificial Intelligence rese...
This paper presents a method of acquiring knowledge from the Web for noun sense disambiguation. Word...
There has been a tradition of combining different knowledge sources in Artificial Intelligence resea...
Word Sense Disambiguation (WSD) aims at making explicit the semantics of a word in context by identi...
Verbs that can have more than one meaning pose problems for Natural Language Processing (NLP) applic...
The SENSEVAL-3 task to perform word-sense disambiguation of WordNet glosses was designed to encourag...
Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowled...
Our system for the Senseval-2 all words task uses automatically acquired selectional preferences to ...
We introduce a new method for unsupervised knowledge-based word sense disambiguation (WSD) based on ...
Our system for the SENSEVAL-2 all words task uses automatically acquired selectional prefer-ences to...
In this paper, we evaluate the results of the Antwerp University word sense disambiguation system in...
In word sense disambiguation (WSD), the heuristic of choosing the most common sense is extremely pow...
Sense tagging, the automatic assignment of the appropriate sense from some lexicon to each of the wo...
In this paper, we evaluate the results of the Antwerp University word sense disambiguation system in...
Domains are common areas of human discussion, such as economics, politics, law, science, etc., which...
There has been a tradition of combining differ-ent knowledge sources in Artificial Intelligence rese...
This paper presents a method of acquiring knowledge from the Web for noun sense disambiguation. Word...
There has been a tradition of combining different knowledge sources in Artificial Intelligence resea...
Word Sense Disambiguation (WSD) aims at making explicit the semantics of a word in context by identi...
Verbs that can have more than one meaning pose problems for Natural Language Processing (NLP) applic...
The SENSEVAL-3 task to perform word-sense disambiguation of WordNet glosses was designed to encourag...
Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowled...
Our system for the Senseval-2 all words task uses automatically acquired selectional preferences to ...
We introduce a new method for unsupervised knowledge-based word sense disambiguation (WSD) based on ...
Our system for the SENSEVAL-2 all words task uses automatically acquired selectional prefer-ences to...
In this paper, we evaluate the results of the Antwerp University word sense disambiguation system in...
In word sense disambiguation (WSD), the heuristic of choosing the most common sense is extremely pow...
Sense tagging, the automatic assignment of the appropriate sense from some lexicon to each of the wo...
In this paper, we evaluate the results of the Antwerp University word sense disambiguation system in...
Domains are common areas of human discussion, such as economics, politics, law, science, etc., which...
There has been a tradition of combining differ-ent knowledge sources in Artificial Intelligence rese...