Papers with distributional methods
Semantic shift in social networks (2021.starsem-1)
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| Challenge: | lexical semantic change manifests differently across different communities, according to a new study . social network analysis is a tool of sociolinguists studying variation and change . |
| Approach: | They use distributional methods to quantify lexical semantic change and induce a social network on communities based on interactions between members. |
| Outcome: | The proposed method is based on interactions between members and the community. |
Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Text (D19-60)
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| Challenge: | Existing work on modeling semantic plausibility has focused on physical plausability but distributional methods fail when tested in supervised settings. |
| Approach: | They propose to use large pretrained language models to model plausibility in supervised settings by extracting attested events from a large corpus and injecting explicit commonsense knowledge into a distributional model. |
| Outcome: | The proposed model is effective in modeling plausibility in a supervised setting. |
Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora (P18-2)
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| Challenge: | a well-known problem of Hearst-like patterns is their extreme sparsity. |
| Approach: | They propose to use pattern-based and distributional methods to perform unsupervised hypernym detection. |
| Outcome: | The proposed method outperforms distributional methods on hypernymy tasks. |
Diachronic word embeddings and semantic shifts: a survey (C18-1)
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| Challenge: | Existing methods for tracing time-related semantic shifts with word embedding models lack the cohesion, common terminology and shared practices of more established areas of natural language processing. |
| Approach: | They propose several axes along which these methods can be compared and propose a framework for comparison. |
| Outcome: | The proposed methods are compared with existing methods and outline their main challenges and potential applications. |
The Effectiveness of Simple Hybrid Systems for Hypernym Discovery (P19-1)
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| Challenge: | Recent work utilizing a mix of pattern-based and distributional approaches have yielded state-of-the-art results on two domain-specific English hypernym discovery tasks. |
| Approach: | They evaluate the contribution of pattern-based and distributional approaches to hybrid modeling by evaluating baseline models from each paradigm. |
| Outcome: | The proposed approach outperforms all non-hybrid approaches on two domain-specific English hypernym discovery tasks and outperformed other approaches. |
When Hearst Is not Enough: Improving Hypernymy Detection from Corpus with Distributional Models (2020.emnlp-main)
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| Challenge: | a taxonomy is a semantic hierarchy of words or concepts organized w.r.t. their hypernymy relationships. |
| Approach: | They propose a framework for hypernymy detection using large textual corpora . they quantify the non-negligible existence of specific sparsity cases . |
| Outcome: | The proposed framework quantifies the non-negligible existence of specific sparsity cases on several benchmark datasets. |