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README.md
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# Data
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One of the paper's core contribution is the construction of B2NERD dataset. It's a cohesive and efficient collection refined from 54 English and Chinese datasets and designed for Open NER model training.
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- `B2NERD` (Recommended): Contain ~52k samples from 54 Chinese or English datasets. This is the final version of our dataset suitable for out-of-domain / zero-shot NER model training. It has standardized entity definitions and pruned diverse data.
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- `B2NERD_all`: Contain ~1.4M samples from 54 datasets. The full-data version of our dataset suitable for in-domain supervised evaluation. It has standardized entity definitions but does not go through any data selection or pruning.
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- `B2NERD_raw`: Raw collected datasets with raw entity labels. It goes through basic format preprocessing but without further standardization.
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# Data
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One of the paper's core contribution is the construction of B2NERD dataset. It's a cohesive and efficient collection refined from 54 English and Chinese datasets and designed for Open NER model training.
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In downloaded file, we provide 3 versions of our dataset.
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- `B2NERD` (Recommended): Contain ~52k samples from 54 Chinese or English datasets. This is the final version of our dataset suitable for out-of-domain / zero-shot NER model training. It has standardized entity definitions and pruned diverse data.
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- `B2NERD_all`: Contain ~1.4M samples from 54 datasets. The full-data version of our dataset suitable for in-domain supervised evaluation. It has standardized entity definitions but does not go through any data selection or pruning.
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- `B2NERD_raw`: Raw collected datasets with raw entity labels. It goes through basic format preprocessing but without further standardization.
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