Eeny, meeny, miny, moe. How to choose data for morphological inflection. (2022.emnlp-main)
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| Challenge: | Data scarcity is a major bottleneck for many natural language processing tasks . active learning aims to reduce the cost of data annotation by selecting the most informative examples to label. |
| Approach: | They propose to use oracle experiments to select data that is most informative for the model. |
| Outcome: | The proposed sampling strategies show that they improve on the oracle experiment and the 10-cycle iteration using Natügu as a case study. |
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| Challenge: | morphological inflection models have been successful with shared tasks . but they fail at generalizing inflation patterns when trained on a limited number of lemmata . |
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