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1
Semi-automatic WordNet Linking using Word Embeddings ...
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2
Indian Language Wordnets and their Linkages with Princeton WordNet ...
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3
Tapping BERT for Preposition Sense Disambiguation ...
Abstract: Prepositions are frequently occurring polysemous words. Disambiguation of prepositions is crucial in tasks like semantic role labelling, question answering, text entailment, and noun compound paraphrasing. In this paper, we propose a novel methodology for preposition sense disambiguation (PSD), which does not use any linguistic tools. In a supervised setting, the machine learning model is presented with sentences wherein prepositions have been annotated with senses. These senses are IDs in what is called The Preposition Project (TPP). We use the hidden layer representations from pre-trained BERT and BERT variants. The latent representations are then classified into the correct sense ID using a Multi Layer Perceptron. The dataset used for this task is from SemEval-2007 Task-6. Our methodology gives an accuracy of 86.85% which is better than the state-of-the-art. ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; I.2.7
URL: https://dx.doi.org/10.48550/arxiv.2111.13972
https://arxiv.org/abs/2111.13972
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4
Techniques for Jointly Extracting Entities and Relations: A Survey ...
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5
Knowledge-based Extraction of Cause-Effect Relations from Biomedical Text ...
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6
How low is too low? A monolingual take on lemmatisation in Indian languages ...
NAACL 2021 2021; Bhattacharyya, Pushpak; Saunack, Kumar. - : Underline Science Inc., 2021
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7
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages ...
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8
M2H2: A Multimodal Multiparty Hindi Dataset For Humor Recognition in Conversations ...
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"So You Think You're Funny?": Rating the Humour Quotient in Standup Comedy ...
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10
Cognition-aware Cognate Detection ...
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11
Role of Language Relatedness in Multilingual Fine­-tuning of Language Models: A Case Study in Indo-­Aryan Languages ...
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12
Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study ...
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13
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages ...
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14
Modelling source- and target-language syntactic Information as conditional context in interactive neural machine translation
In: Gupta, Kamal Kumar, Haque, Rejwanul orcid:0000-0003-1680-0099 , Ekbal, Asif, Bhattacharyya, Pushpak and Way, Andy orcid:0000-0001-5736-5930 (2020) Modelling source- and target-language syntactic Information as conditional context in interactive neural machine translation. In: Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 2-6 Nov 2020, Lisboa, Portugal. (2020)
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15
Syntax-informed interactive neural machine translation
In: Gupta, Kamal Kumar, Haque, Rejwanul orcid:0000-0003-1680-0099 , Ekbal, Asif, Bhattacharyya, Pushpak and Way, Andy orcid:0000-0001-5736-5930 (2020) Syntax-informed interactive neural machine translation. In: The International Joint Conference on Neural Networks (IJCNN), 19-24 July 2020, Glasgow, UK (Online). (2020)
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16
Extracting N-ary Cross-sentence Relations using Constrained Subsequence Kernel ...
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17
Related Tasks can Share! A Multi-task Framework for Affective language ...
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18
Reinforced Multi-task Approach for Multi-hop Question Generation ...
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19
Utilizing Language Relatedness to improve Machine Translation: A Case Study on Languages of the Indian Subcontinent ...
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20
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages ...
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