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  1. README.md +8 -5
README.md CHANGED
@@ -11,12 +11,9 @@ tags:
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  - legal
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  - law
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  size_categories:
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- - 100K<n<1M
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  ---
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- README in progress
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-
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-
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  # Usage
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  The dataset is in folder according to the task and type (e.g. `generation` or `collection` for IR).
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@@ -26,4 +23,10 @@ from datasets import load_dataset
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  dataset = load_dataset("jhu-clsp/CLERC", data_files={"data": f"generation/test.jsonl"})["data"]
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  ```
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- Change the values in `data_files` to match the file you want to load.
 
 
 
 
 
 
 
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  - legal
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  - law
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  size_categories:
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+ - 1M<n<10M
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  ---
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  # Usage
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  The dataset is in folder according to the task and type (e.g. `generation` or `collection` for IR).
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  dataset = load_dataset("jhu-clsp/CLERC", data_files={"data": f"generation/test.jsonl"})["data"]
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  ```
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+ # Dataset Description:
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+ CLERC is a large-scale dataset of federal case law from the paper (https://arxiv.org/abs/2406.17186). It has a few subsets:
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+ 1. collection: records 1.84M original federal case law, both in doc and passage forms. This can be used for doing retrieval or alternative tasks.
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+ 2. generation: includes data for the RAG task as described in the paper. Also see the github (https://github.com/bohanhou14/CLERC) for more details.
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+ 3. qrels and queries: qrels and queries used for the retrieval task, all following MSMARCO formats.
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+ 4. triples, teva_train_triples: triples in different formats for evaluation and training (with tevatron)
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+