Enough Is Enough! a Case Study on the Effect of Data Size for Evaluation Using Universal Dependencies (2024.lrec-main)
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| Challenge: | a recent study suggests that large datasets require large amounts of simulated data and scores to perform model evaluation. |
| Approach: | They propose to use dependency parsing to optimize annotation efforts by using a sample size of 5,000 tokens for in-language in-domain datasets. |
| Outcome: | The proposed method can be applied to other tasks, including classification and translation tasks. |
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