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Word Sense Disambiguation

42 papers with code · Natural Language Processing

The task of Word Sense Disambiguation (WSD) consists of associating words in context with their most suitable entry in a pre-defined sense inventory. The de-facto sense inventory for English in WSD is WordNet. For example, given the word “mouse” and the following sentence:

“A mouse consists of an object held in one's hand, with one or more buttons.”

we would assign “mouse” with its electronic device sense (the 4th sense in the WordNet sense inventory).

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Greatest papers with code

FlauBERT: Unsupervised Language Model Pre-training for French

LREC 2020 huggingface/transformers

Language models have become a key step to achieve state-of-the art results in many different Natural Language Processing (NLP) tasks.

LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE TEXT CLASSIFICATION WORD SENSE DISAMBIGUATION

Language Models are Few-Shot Learners

28 May 2020openai/gpt-3

By contrast, humans can generally perform a new language task from only a few examples or from simple instructions - something which current NLP systems still largely struggle to do.

 SOTA for Language Modelling on Penn Treebank (Word Level) (using extra training data)

COMMON SENSE REASONING COREFERENCE RESOLUTION DOMAIN ADAPTATION FEW-SHOT LEARNING LANGUAGE MODELLING NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SENTENCE COMPLETION UNSUPERVISED MACHINE TRANSLATION WORD SENSE DISAMBIGUATION

Incorporating Glosses into Neural Word Sense Disambiguation

ACL 2018 jimiyulu/WSD_MemNN

GAS models the semantic relationship between the context and the gloss in an improved memory network framework, which breaks the barriers of the previous supervised methods and knowledge-based methods.

WORD SENSE DISAMBIGUATION

Zero-shot Word Sense Disambiguation using Sense Definition Embeddings

ACL 2019 malllabiisc/EWISE

To overcome this challenge, we propose Extended WSD Incorporating Sense Embeddings (EWISE), a supervised model to perform WSD by predicting over a continuous sense embedding space as opposed to a discrete label space.

KNOWLEDGE GRAPH EMBEDDING WORD SENSE DISAMBIGUATION ZERO-SHOT LEARNING

GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge

IJCNLP 2019 HSLCY/GlossBERT

Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous word in a particular context.

WORD SENSE DISAMBIGUATION

LIAAD at SemDeep-5 Challenge: Word-in-Context (WiC)

WS 2019 danlou/LMMS

This paper describes the LIAAD system that was ranked second place in the Word-in-Context challenge (WiC) featured in SemDeep-5.

WORD SENSE DISAMBIGUATION