Papers with word meaning
Adverbs, Surprisingly (2023.starsem-1)
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| Challenge: | adverbs are the part of speech (POS) that has seen the least attention in computational linguistics due to its challenging nature. |
| Approach: | They propose to use Frame Semantics to characterize word meaning to uncover systematic gaps in adverb accounts. |
| Outcome: | The proposed approach can describe ambiguity, semantic roles, and null instantiation of adverbs. |
Interpretable Word Sense Representations via Definition Generation: The Case of Semantic Change Analysis (2023.acl-long)
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| Challenge: | Existing approaches to semantic change analysis are limited in their interpretation power and lack of explanatory power. |
| Approach: | They propose to use specialised Flan-T5 language models to generate a definition for each usage and a specialised word sense model to generate the most prototypical definition. |
| Outcome: | The proposed representations outperform token or usage sentence embeddings in word-in-context semantic similarity judgements and are a promising type of lexical representation for NLP. |
Word Embedding-Based Automatic MT Evaluation Metric using Word Position Information (N19-1)
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| Challenge: | Existing evaluation metrics for machine translation are difficult to address word meaning because it is a surface-level metric. |
| Approach: | They propose to use word embeddings, sentence-level tf-idf, and cosine similarity between two word embeds as features, weight, and the distance between two features as features. |
| Outcome: | The proposed metric can evaluate machine translation based on word meaning . it achieves highest correlation with human judgment among several representative metrics. |