Papers with English WordNet

8 papers
Metaphorical Polysemy Detection: Conventional Metaphor Meets Word Sense Disambiguation (2022.coling-1)

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Challenge: Linguists distinguish between novel and conventional metaphors, a distinction which the metaphor detection task in NLP does not take into account.
Approach: They propose a method which treats conventional metaphors as a property of word senses in a lexicon and combines metaphor detection with word sense disambiguation to train it.
Outcome: The proposed model outperforms a state-of-the-art model in annotating metaphor in two subsets of WordNet and achieves .78 ROC-AUC score compared to baseline model .
Annotating Chinese Word Senses with English WordNet: A Practice on OntoNotes Chinese Sense Inventories (2024.lrec-main)

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Challenge: a recent study has shown that large language models can be useful for cross-lingual applications.
Approach: They propose to annotate Chinese word senses using English WordNet synsets . they examine the relationship between two annotators and find patterns among synset .
Outcome: The proposed method shows that the annotators agree on 38% of the synsets compared with the original synset . the results highlight similarities between the synnotated synset and the WordNet structure .
Are Large Language Models Good at Lexical Semantics? A Case of Taxonomy Learning (2024.lrec-main)

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Challenge: Recent studies on LLMs do not pay enough attention to linguistic and lexical semantic tasks, such as taxonomy learning.
Approach: They propose a method for stochastic graph traversal and a new algorithm for data collection . they propose LLaMA-2 and Mistral for a lexical semantic task .
Outcome: The proposed models can perform linguistic and lexical tasks, but they lack basic skills in taxonomy learning.
Huge Automatically Extracted Training-Sets for Multilingual Word SenseDisambiguation (L18-1)

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Challenge: Word Sense Disambiguation is a crucial task in Natural Language Processing . supervised systems need to be trained on word-by-word basis, a problem that is beyond reach for resource-rich languages like English.
Approach: They release six large-scale sense-annotated datasets in multiple languages to pave the way for supervised multilingual Word Sense Disambiguation.
Outcome: The results show that large-scale sense annotations can be used as training sets for supervised systems.
Constructing Taxonomies from Pretrained Language Models (2021.naacl-main)

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Challenge: A variety of NLP tasks use taxonomic information, including question answering and information retrieval.
Approach: They propose a method for constructing taxonomic trees using pretrained language models by incorporating web-retrieved glosses into the model.
Outcome: The proposed model achieves 66.7 ancestor F1, a 20.0% relative increase over the previous best published model on English WordNet.
Preserving Semantic Information from Old Dictionaries: Linking Senses of the ‘Altfranzösisches Wörterbuch’ to WordNet (2020.lrec-1)

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Challenge: Historical dictionaries of the pre-digital period are important resources for the study of older languages.
Approach: They propose to use printed dictionaries to create a more easily accessible and more sustainable lexical database by automating the conversion process.
Outcome: The ‘Altfranzösisches Wörterbuch’, an Old French dictionary published from 1925 onwards, shows how the printed dictionaries can be turned into a more easily accessible and more sustainable lexical database.
Towards the Construction of a WordNet for Old English (2022.lrec-1)

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Challenge: In this paper we discuss our preliminary work towards the construction of a WordNet for Old English, taking our inspiration from other similar WN construction projects for ancient languages such as Ancient Greek, Latin and Sanskrit.
Approach: They propose to use a legacy Old English dictionary to build a WordNet for Old English using a lexicographic resource and the naisc system to automatically compile a provisional version of the WordNet.
Outcome: The proposed OldEWN will be based on lemmas and definitions extracted from a legacy Old English dictionary and will be automatically compile and enriched by experts using the naisc system.
English WordNet Random Walk Pseudo-Corpora (2020.lrec-1)

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Challenge: a random walk over the WordNet taxonomy generates a set of pseudo-corpora . a resource description paper describes the creation and properties of such pseudo-corporates .
Approach: They propose to use random walk to generate a set of pseudo-corpora over the English WordNet taxonomy.
Outcome: The proposed pseudo-corpora can be used to train taxonomic word embeddings . the proposed pseudo corpora are generated from a random walk over the English wordnet taxonomy .

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