Broad-Coverage Hierarchical Word Sense Disambiguation
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چکیده
منابع مشابه
Getting Serious About Word Sense Disambiguation
Recent advances in large-scale, broad coverage part-of-speech tagging and syntactic parsing have been achieved in no small part due to the availability of large amounts of online, human-annotated corpora. In this paper, I argue that a large, human sensetagged corpus is also critical as well as necessary to achieve broad coverage, high accuracy word sense disambiguation, where the sense distinct...
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Word sense disambiguation is the process of determining which sense of a word is used in a given context. Due to its importance in understanding semantics of natural languages, word sense disambiguation has been extensively studied in Computational Linguistics. However, existing methods either are brittle and narrowly focus on specific topics or words, or provide only mediocre performance in re...
متن کاملInvited Talk: The Relevance of a Cognitive Model of the Mental Lexicon to Automatic Word Sense Disambiguation
Supervised word sense disambiguation requires training corpora that have been tagged with word senses, and these word senses typically come from a pre-existing sense inventory. Space limitations imposed by dictionary publishers have biased the field towards lists of discrete senses for an individual lexeme. Although some dictionaries use hierarchical entries to emphasize relations between sense...
متن کاملBroad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger
This paper presents a novel approach to broad-coverage word sense disambiguation and information extraction. The task consists of annotating text with the tagset defined by the 41 Wordnet supersense classes for nouns and verbs. Since the tagset is directly related to Wordnet synsets, the tagger returns partial word sense disambiguation. Furthermore, since the noun tags include the standard name...
متن کاملSyntactic Features for High Precision Word Sense Disambiguation
This paper explores the contribution of a broad range of syntactic features to WSD: grammatical relations coded as the presence of adjuncts/arguments in isolation or as subcategorization frames, and instantiated grammatical relations between words. We have tested the performance of syntactic features using two different ML algorithms (Decision Lists and AdaBoost) on the Senseval-2 data. Adding ...
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تاریخ انتشار 2005