A Combined Approach Using Semantic Role Labelling and Word Sense Disambiguation for Question Generation and Answer Extraction

Pillai, Lekshmi R; Veena, G; Gupta, Deepa

doi:10.1109/icaecc.2018.8479468

Cited by 19 publications

(9 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is primarily because the existing techniques used by the system cannot address the effectiveness and efficiency of semantic issues in their NLQ analysis. Some scholars [11,79,80] reported positive outcomes to lexical solutions on the topic of word sense disambiguation (WSD), and several studies [42,62] appraised this issue in the context of QA, but only a few examined the role of WSD when returning potential answers [12,81].…”

Section: The Challenges Of the Qa Systemmentioning

confidence: 99%

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Arbaaeen

Shah

2021

Information

View full text Add to dashboard Cite

For many users of natural language processing (NLP), it can be challenging to obtain concise, accurate and precise answers to a question. Systems such as question answering (QA) enable users to ask questions and receive feedback in the form of quick answers to questions posed in natural language, rather than in the form of lists of documents delivered by search engines. This task is challenging and involves complex semantic annotation and knowledge representation. This study reviews the literature detailing ontology-based methods that semantically enhance QA for a closed domain, by presenting a literature review of the relevant studies published between 2000 and 2020. The review reports that 83 of the 124 papers considered acknowledge the QA approach, and recommend its development and evaluation using different methods. These methods are evaluated according to accuracy, precision, and recall. An ontological approach to semantically enhancing QA is found to be adopted in a limited way, as many of the studies reviewed concentrated instead on NLP and information retrieval (IR) processing. While the majority of the studies reviewed focus on open domains, this study investigates the closed domain.

show abstract

Section: The Challenges Of the Qa Systemmentioning

confidence: 99%

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Arbaaeen

Shah

2021

Information

View full text Add to dashboard Cite

show abstract

“…The Lesk tool has been used for WSD where the senna tool has been used for SRL. They used Lesk tool for WSD and senna tool for SRL which are based on the sense affiliated with the sentence system generates questions that are semantically solvable as in [26]. Word sense disambiguation can be solved using three kinds of approaches, knowledge based, corpus based and hybrid approach.…”

Section: Related Workmentioning

confidence: 99%

“…Lekshmi R Pillai et al [26] Word Sense Disambiguation for Question-Answering System [26] This is a factoid sense based questionanswering system. The WSD and Semantic Role Labelling (SRL) approaches have been applied on this system.…”

Section: Authors Wsd Based Systems Technique(s) Used In Similar Type ...mentioning

confidence: 99%

Word Sense Disambiguation in Hindi Language Using Score Based Modified Lesk Algorithm

Tripathi¹,

Mukherjee²,

Hendre³

et al. 2021

IJCDS

View full text Add to dashboard Cite

Hindi is the widely used spoken language in the Indian subcontinent, and is used by more than 260 million Indians citizens. Indian governments has many digital initiatives to serve Indian citizen better, hence Hindi language becomes one of the important languages to serve Indian citizen. The Government initiatives are like smart city, Hospital Services, Common Service Centers, Digital Payment Ecosystem, Pensioners Scheme, Digital Locker and many more. These all initiative are served using mobile and web based applications, which citizens can access easily instead of visiting various government departments. To serve the large Hindi speaking population, it is necessary to handle the ambiguous words which have multiple connotations in any natural language processing task. In this paper, word sense disambiguation for Hindi language is proposed. Proposed method makes use of Lesk algorithm to disambiguate the Hindi words. Novel scoring method is used to assign a sense score to each token of the Hindi sentence. The sense score is calculated based on the gloss, hypernym, hyponym and synonym of the combinations of different sense of tokens. Hindi WordNet database created by CFILT, IIT Bombay is used in the proposed system. The proposed algorithm takes a natural language (NL) sentence in Hindi (Devanagari script) and process the sentence according to the score based approach modeled on the basic Lesk algorithm with the help of Hindi WordNet designed by CFILT IIT Bombay. The solution provided in this paper can be used vividly in various web based applications like Query-Response Systems, Question-Answer Systems, Sentiment analysis, Recommendation systems etc.

show abstract

“…The predicate-argument structure associated with the QA system denotes P(SRLs), where P represents the predicate, and the SRLs is a group of semantic role labels. The initial syntactic analysis is crucial, which assists to determine arguments associated with the predicate of the NL question [14]. In this study, nouns are considered as arguments associated with a verb type predicate of the NL question.…”

Section: Semantic Role Labellingmentioning

confidence: 99%

“…A close look at the relevant literature reveals that researchers [11,12] have reported progressive results to lexical issues on the topic of word sense disambiguation (WSD). In addition, several studies [9,13] have appraised this problem in the context of question answering, however, challenging questions may require handling ambiguities based on date and location-specific to certain conditions, such as seeking instructions or advice in a critical situation [1,8,14]. For instance, a user posed a question: What are the hajj pillars?…”

Section: Introductionmentioning

confidence: 99%

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

Arbaaeen

Shah

2021

Information

View full text Add to dashboard Cite

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.

show abstract

A Combined Approach Using Semantic Role Labelling and Word Sense Disambiguation for Question Generation and Answer Extraction

Cited by 19 publications

References 2 publications

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Word Sense Disambiguation in Hindi Language Using Score Based Modified Lesk Algorithm

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

Contact Info

Product

Resources

About