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README.md
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@@ -12,7 +12,7 @@ Our B2NER models, trained on B2NERD, outperform GPT-4 by 6.8-12.0 F1 points and
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- ๐ Paper: [Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition](http://arxiv.org/abs/2406.11192)
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- ๐ฎ Github Repo: https://github.com/UmeanNever/B2NER
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- ๐ Data: See below data section. You can download from here (Files) or [Google Drive](https://drive.google.com/file/d/11Wt4RU48i06OruRca2q_MsgpylzNDdjN/view?usp=drive_link).
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- ๐พ Model (LoRA Adapters): On the way
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See github repo for more information about data usage and this work.
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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 undergo any data selection or pruning.
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- `B2NERD_raw`: The raw collected datasets with raw entity labels. It goes through basic format preprocessing but without further standardization.
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You can download the data from
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Please ensure that you have the proper licenses to access the raw datasets in our collection.
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Below are the datasets statistics and source datasets for `B2NERD` dataset.
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- ๐ Paper: [Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition](http://arxiv.org/abs/2406.11192)
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- ๐ฎ Github Repo: https://github.com/UmeanNever/B2NER
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- ๐ Data: See below data section. You can download from here (in "Files and versions" tab) or [Google Drive](https://drive.google.com/file/d/11Wt4RU48i06OruRca2q_MsgpylzNDdjN/view?usp=drive_link).
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- ๐พ Model (LoRA Adapters): On the way
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See github repo for more information about data usage and this work.
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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 undergo any data selection or pruning.
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- `B2NERD_raw`: The raw collected datasets with raw entity labels. It goes through basic format preprocessing but without further standardization.
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You can download the data from here (in "Files and versions" tab) or [Google Drive](https://drive.google.com/file/d/1JW3ZZPlJ5vm_upn0msihI9FQjo4TmZDI/view?usp=sharing). Current data is uploaded as .zip for convenience. We are considering upload raw data files for better preview.
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Please ensure that you have the proper licenses to access the raw datasets in our collection.
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Below are the datasets statistics and source datasets for `B2NERD` dataset.
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