Refining the Distributional Inclusion Hypothesis for Unsupervised Hypernym Identification
Several unsupervised methods for hypernym detection have been investigated in distributional semantics. Here we present a new approach based on a smoothed version of the distributional inclusion hypothesis. The new method is able to improve hypernym detection after testing on the BLESS dataset.
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Accademia University Press
2018-12-01
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| Series: | IJCoL |
| Online Access: | https://journals.openedition.org/ijcol/506 |
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| Summary: | Several unsupervised methods for hypernym detection have been investigated in distributional semantics. Here we present a new approach based on a smoothed version of the distributional inclusion hypothesis. The new method is able to improve hypernym detection after testing on the BLESS dataset. |
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| ISSN: | 2499-4553 |