Papers by Girish Palshikar
FrameNet-assisted Noun Compound Interpretation (2021.findings-acl)
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| Challenge: | Existing methods for predicting semantic labels for noun compound interpretation are difficult. |
| Approach: | They propose to predict semantic labels in a continuous embedding space using FrameNet data. |
| Outcome: | The proposed method performs well on unseen labels, with 5% and 2% improvement over baselines for frame and FE prediction. |
Treat us like the sequences we are: Prepositional Paraphrasing of Noun Compounds using LSTM (C18-1)
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| Challenge: | Using prepositions, noun compounds are interpreted in two ways: labelling and paraphrasing. |
| Approach: | They propose to paraphrase noun compounds using prepositions by using parallelly aligned sequences of words. |
| Outcome: | The proposed approach performs well on datasets manually annotated with prepositions. |
Looking inside Noun Compounds: Unsupervised Prepositional and Free Paraphrasing (2020.findings-emnlp)
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| Challenge: | Noun compound interpretation is the task of uncovering the semantic relation between the components of a noun compound. |
| Approach: | They propose an unsupervised method for identifying such relations between the components of a noun compound using pre-trained contextualized language models. |
| Outcome: | The proposed method outperforms supervised approaches for free paraphrasing and prepositional paraphrases using pre-trained language models to uncover ‘missing’ words. |
Why Generate When You Can Discriminate? A Novel Technique for Text Classification using Language Models (2024.findings-eacl)
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| Challenge: | Existing methods for text classification using autoregressive language models are limited . authors propose a novel technique for text classification using autoreregressives . |
| Approach: | They propose a two-step technique for text classification using autoregressive language models . they use a set of perplexity and log-likelihood based numeric features to elicit a text instance . |
| Outcome: | The proposed technique eliminates parameter updates in LMs and does not limit training examples . it is evaluated across 5 datasets and compares with multiple competent baselines . |
Constructing A Dataset of Support and Attack Relations in Legal Arguments in Court Judgements using Linguistic Rules (2022.lrec-1)
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| Challenge: | Argumentation mining is a growing area of research with several interesting practical applications. |
| Approach: | They propose three sets of rules based on linguistic knowledge and distant supervision to identify such relations from Indian Supreme Court judgments. |
| Outcome: | The proposed rules are based on linguistic knowledge and distant supervision and use the source of the argument to build a dataset of Support and Attack relations between sentences in a court judgement with reasonable accuracy. |
Generating An Optimal Interview Question Plan Using A Knowledge Graph And Integer Linear Programming (2021.naacl-main)
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| Challenge: | a large multi-national IT company added roughly 70,000 employees in FY2018-19. |
| Approach: | They propose an interview assistant system to automatically select an optimal set of technical questions personalized for a candidate. |
| Outcome: | The proposed system can help human interviewers plan for an upcoming interview of that candidate. |
Extraction of Message Sequence Charts from Software Use-Case Descriptions (N19-2)
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Girish Palshikar, Nitin Ramrakhiyani, Sangameshwar Patil, Sachin Pawar, Swapnil Hingmire, Vasudeva Varma, Pushpak Bhattacharyya
| Challenge: | Software Requirement Specification documents provide natural language descriptions of the core functional requirements as a set of use-cases. |
| Approach: | They propose a linguistic knowledge-based approach to extract software requirements from use-cases using a textual representation of the core functional requirements. |
| Outcome: | The proposed method performs better than existing techniques and improves performance. |
Identification of Alias Links among Participants in Narratives (P18-2)
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Sangameshwar Patil, Sachin Pawar, Swapnil Hingmire, Girish Palshikar, Vasudeva Varma, Pushpak Bhattacharyya
| Challenge: | Identifying distinct and independent participants in a narrative is crucial for many NLP applications. |
| Approach: | They propose an approach based on linguistic knowledge for identification of aliases mentioned using proper nouns, pronouns or noun phrases with common noun headword. |
| Outcome: | The proposed approach performs better than the state-of-the-art approach on four diverse history narratives of varying complexity. |