Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis (2020.coling-main)
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| Challenge: | Existing methods to learn general language representations from large volumes of unlabeled text have been used to improve multilingual NLP. |
| Approach: | They propose to use a spatial arrangement method to generate large-scale evaluation datasets that balance cross-lingual alignment with language specificity. |
| Outcome: | The proposed method produces semantic verb classes and fine-grained similarity scores for nearly 130 thousand verb pairs. |
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