Domain-specific Evaluation of Word Embeddings for Philosophical Text using Direct Intrinsic Evaluation
| Authors | |
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| Publication date | 2022 |
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| Book title | The 2nd International Workshop on Natural Language Processing for Digital Humanities |
| Book subtitle | proceedings of the workshop : NLP4DH 2021 : November 20, 2022 |
| ISBN (electronic) |
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| Event | 2nd International Workshop on Natural Language Processing for Digital Humanities (NLP4DH) |
| Pages (from-to) | 101-107 |
| Number of pages | 7 |
| Publisher | Stroudsburg, PA: Association for Computational Linguistics |
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| Abstract | We perform a direct intrinsic evaluation of word embeddings trained on the works of a single philosopher. Six models are compared to human judgements elicited using two tasks: a synonym detection task and a coherence task. We apply a method that elicits judgements based on explicit knowledge from experts, as the linguistic intuition of non-expert participants might differ from that of the philosopher. We find that an in-domain SVD model has the best 1-nearest neighbours for target terms, while transfer learning-based Nonce2Vec performs better for low frequency target terms. |
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.18653/v1/2022.nlp4dh-1.14 |
| Downloads |
2022.nlp4dh-1.14
(Final published version)
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