Extracting Conjunction Patterns in Relation Triplets from Complex Requirement Sentence
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2018 by IJCTT Journal | ||
| Volume-60 Number-3 |
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| Year of Publication : 2018 | ||
| Authors : Veera Prathap Reddy M, Prasad P.V.R.D, Manjunath Chikkamath, Karthikeyan Ponnalagu | ||
| DOI : 10.14445/22312803/IJCTT-V60P121 |
Veera Prathap Reddy M, Prasad P.V.R.D, Manjunath Chikkamath, Karthikeyan Ponnalagu "Extracting Conjunction Patterns in Relation Triplets from Complex Requirement Sentence". International Journal of Computer Trends and Technology (IJCTT) V60(3):133-143 June 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract
Automatically extracting knowledge from complex unstructured software requirement sentences is an important research challenge. The objective would be reducing human interpretation errors that contribute to more than 50% of overall software defects. In this paper, we propose pattern based open information extraction (OIE) approach towards addressing this challenge. Our proposed approach extracts meaningful relations from natural language sentences that are considered complex with conjunctive (correlative, coordinating and subordinating) structures. Our proposed approach exploits linguistic knowledge about English language grammar to identify pattern in requirement sentence and subsequently extract information according to the grammatical function of its constituents. We propose MRAlgo, an automated multiple-relation Verb centric information extraction algorithm specifically for software requirement engineering domain that can detect every action, subject and object when linked with conjunctions. We have evaluated MRAlgo by a random sample of sentences selected from public dataset of requirement sentences having conjunctive nature and few sentences from web, and obtained high precision and recall when compared to other Open information extraction approaches
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Keywords
Multiple-relation extraction, Natural Language Processing (NLP), dependency parser, verbbased algorithm.