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albertvillanova HF staff commited on
Commit
788845f
1 Parent(s): 72112ee

Add light data files

Browse files
README.md CHANGED
@@ -84,13 +84,13 @@ dataset_info:
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  sequence: string
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  splits:
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  - name: train
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- num_bytes: 2739732
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  num_examples: 10036
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  - name: validation
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- num_bytes: 805808
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  num_examples: 2002
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- download_size: 19700900
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- dataset_size: 3545540
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  configs:
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  - config_name: full
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  data_files:
@@ -99,6 +99,12 @@ configs:
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  - split: validation
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  path: full/validation-*
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  default: true
 
 
 
 
 
 
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  ---
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  # Dataset Card for AmbigQA: Answering Ambiguous Open-domain Questions
 
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  sequence: string
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  splits:
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  - name: train
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+ num_bytes: 2739628
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  num_examples: 10036
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  - name: validation
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+ num_bytes: 805756
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  num_examples: 2002
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+ download_size: 1777867
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+ dataset_size: 3545384
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  configs:
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  - config_name: full
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  data_files:
 
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  - split: validation
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  path: full/validation-*
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  default: true
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+ - config_name: light
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+ data_files:
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+ - split: train
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+ path: light/train-*
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+ - split: validation
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+ path: light/validation-*
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  ---
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  # Dataset Card for AmbigQA: Answering Ambiguous Open-domain Questions
dataset_infos.json CHANGED
@@ -7,66 +7,50 @@
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  "features": {
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  "id": {
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  "dtype": "string",
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- "id": null,
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  "_type": "Value"
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  },
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  "question": {
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  "dtype": "string",
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- "id": null,
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  "_type": "Value"
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  },
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  "annotations": {
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  "feature": {
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  "type": {
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  "dtype": "string",
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- "id": null,
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  "_type": "Value"
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  },
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  "answer": {
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  "feature": {
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  "dtype": "string",
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- "id": null,
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  "_type": "Value"
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- "length": -1,
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  "_type": "Sequence"
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  },
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  "qaPairs": {
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  "feature": {
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  "question": {
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  "dtype": "string",
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  "_type": "Value"
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  "answer": {
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  "_type": "Sequence"
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  },
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- "post_processed": null,
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- "supervised_keys": null,
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- "builder_name": "ambig_qa",
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  "config_name": "light",
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  "version": {
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  "version_str": "1.0.0",
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- "description": null,
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  "major": 1,
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  "minor": 0,
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  "patch": 0
@@ -74,31 +58,20 @@
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  "splits": {
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  "train": {
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  "name": "train",
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- "num_bytes": 2739732,
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  "num_examples": 10036,
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- "dataset_name": "ambig_qa"
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  },
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  "validation": {
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  "name": "validation",
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- "num_bytes": 805808,
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  "num_examples": 2002,
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- "dataset_name": "ambig_qa"
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- }
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- },
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- "download_checksums": {
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- "https://nlp.cs.washington.edu/ambigqa/data/ambignq_light.zip": {
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- "checksum": "3f5dada69dec05cef1533a64945cd7bafde1aa94b0cdd6fa9a22f881206220db"
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- "https://nlp.cs.washington.edu/ambigqa/data/ambignq.zip": {
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- "checksum": "e85cec5909f076c6f584322c7f05cae44dcacaec93758c110a26fcceaa8da0ce"
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  }
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  },
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- "download_size": 19700900,
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- "post_processing_size": null,
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- "dataset_size": 3545540,
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- "size_in_bytes": 23246440
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  },
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  "full": {
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  "description": "AmbigNQ, a dataset covering 14,042 questions from NQ-open, an existing open-domain QA benchmark. We find that over half of the questions in NQ-open are ambiguous. The types of ambiguity are diverse and sometimes subtle, many of which are only apparent after examining evidence provided by a very large text corpus. AMBIGNQ, a dataset with\n14,042 annotations on NQ-OPEN questions containing diverse types of ambiguity.\nWe provide two distributions of our new dataset AmbigNQ: a full version with all annotation metadata and a light version with only inputs and outputs.\n",
 
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  "features": {
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  "id": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
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  "question": {
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  "dtype": "string",
 
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  "_type": "Value"
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  "annotations": {
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  "feature": {
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  "type": {
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  "_type": "Value"
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  },
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  "answer": {
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  "feature": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
 
 
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  "_type": "Sequence"
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  },
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  "qaPairs": {
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  "feature": {
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  "question": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
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  "answer": {
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  "feature": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
 
 
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  "_type": "Sequence"
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  },
 
 
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  "_type": "Sequence"
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  }
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  },
 
 
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  "_type": "Sequence"
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  }
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  },
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+ "builder_name": "parquet",
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+ "dataset_name": "ambig_qa",
 
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  "config_name": "light",
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  "version": {
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  "version_str": "1.0.0",
 
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  "major": 1,
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  "minor": 0,
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  "patch": 0
 
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  "splits": {
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  "train": {
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  "name": "train",
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+ "num_bytes": 2739628,
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  "num_examples": 10036,
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+ "dataset_name": null
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  },
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  "validation": {
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  "name": "validation",
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+ "num_bytes": 805756,
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  "num_examples": 2002,
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+ "dataset_name": null
 
 
 
 
 
 
 
 
 
 
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  }
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  },
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+ "download_size": 1777867,
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+ "dataset_size": 3545384,
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+ "size_in_bytes": 5323251
 
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  },
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  "full": {
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  "description": "AmbigNQ, a dataset covering 14,042 questions from NQ-open, an existing open-domain QA benchmark. We find that over half of the questions in NQ-open are ambiguous. The types of ambiguity are diverse and sometimes subtle, many of which are only apparent after examining evidence provided by a very large text corpus. AMBIGNQ, a dataset with\n14,042 annotations on NQ-OPEN questions containing diverse types of ambiguity.\nWe provide two distributions of our new dataset AmbigNQ: a full version with all annotation metadata and a light version with only inputs and outputs.\n",
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