Word Sense Disambiguation Using WSD Specific Wordnet of Polysemy Words

Dhungana, Udaya Raj; Shakya, Subarna; Baral, Kabita

doi:10.5121/ijnlc.2014.3405

Cited by 7 publications

(2 citation statements)

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“…The domain of the context is compared to the target word's senses in order to disambiguate words by using the external context knowledge such as WordNet. Although WordNet covers a wide range of words and semantic relations, It is limited in words availability and domain-specific terminology in its database [38]. Therefore, the ontology of the domain' concept beside the WordNet domain is used in this work to assist in lexical disambiguation processing.…”

Section: Context Knowledgementioning

confidence: 99%

A Knowledge-Based Sense Disambiguation Method to Semantically Enhanced NL Question for Restricted Domain

Arbaaeen

Shah

2021

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Within the space of question answering (QA) systems, the most critical module to improve overall performance is question analysis processing. Extracting the lexical semantic of a Natural Language (NL) question presents challenges at syntactic and semantic levels for most QA systems. This is due to the difference between the words posed by a user and the terms presently stored in the knowledge bases. Many studies have achieved encouraging results in lexical semantic resolution on the topic of word sense disambiguation (WSD), and several other works consider these challenges in the context of QA applications. Additionally, few scholars have examined the role of WSD in returning potential answers corresponding to particular questions. However, natural language processing (NLP) is still facing several challenges to determine the precise meaning of various ambiguities. Therefore, the motivation of this work is to propose a novel knowledge-based sense disambiguation (KSD) method for resolving the problem of lexical ambiguity associated with questions posed in QA systems. The major contribution is the proposed innovative method, which incorporates multiple knowledge sources. This includes the question’s metadata (date/GPS), context knowledge, and domain ontology into a shallow NLP. The proposed KSD method is developed into a unique tool for a mobile QA application that aims to determine the intended meaning of questions expressed by pilgrims. The experimental results reveal that our method obtained comparable and better accuracy performance than the baselines in the context of the pilgrimage domain.

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Section: Context Knowledgementioning

confidence: 99%

A Knowledge-Based Sense Disambiguation Method to Semantically Enhanced NL Question for Restricted Domain

Arbaaeen

Shah

2021

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“…For these reasons, use of glosses of relatives of a word in higher level is not appropriate and the definitions in the WordNet still don't contain sufficient information for sense disambiguation. The results from experiments indicate the higher level hypernyms/hyponyms are not useful for all words for sense disambiguation [10], [19], [20]. Very few words are overlapped with context, even the full hypernymy hierarchy from WordNet is used for word sense disambiguation [11].…”

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confidence: 99%

PolyWordNet: Analogous to Human Mind for Word Sense Disambiguation

Dhungana¹,

Shakya²

2020

IJCDS

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PolyWordNet is a new lexical database which deals with the organization of senses of polysemy words. It mimics the way how human mind organizes the senses of polysemy words and their related words to analyze and determine correct meaning of a polysemy word in a context. A related word of a sense of a polysemy word is a word which provides necessary and sufficient context to disambiguate the meaning of the polysemy word. A context with a polysemy word must contain at least one related word that determines the correct sense of the polysemy word. The PolyWordNet utilizes this fact to organize the senses of a polysemy word with their corresponding related words. PolyWordNet is completely different than that of the dictionary and WordNet. The words which spell similar come together in dictionary. The words with similar meaning come together in WordNet. The same words, in WordNet, are connected to the multiple senses of the same polysemy word. This introduces an ambiguity. This ambiguity is resolved in PolyWordNet by linking one related word only with a single sense of the same polysemy word. The PolyWordNet can be used to disambiguate senses of polysemy words more precisely and more efficiently.

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