Dataset Preview

The dataset preview is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    NotImplementedError
Message:      os.path.isdir is not extended to support URLs in streaming mode
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/responses/first_rows.py", line 337, in get_first_rows_response
                  rows = get_rows(dataset, config, split, streaming=True, rows_max_number=rows_max_number, hf_token=hf_token)
                File "/src/services/worker/src/worker/utils.py", line 123, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/responses/first_rows.py", line 65, in get_rows
                  ds = load_dataset(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1739, in load_dataset
                  return builder_instance.as_streaming_dataset(split=split)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1025, in as_streaming_dataset
                  splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
                File "/tmp/modules-cache/datasets_modules/datasets/docred/d4f4edf2eb07bc25014d2fb7c9ac0292b65a34ab9195a8e1a738e63e3153a751/docred.py", line 80, in _split_generators
                  if os.path.isdir(downloads[key]):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 67, in wrapper
                  return function(*args, use_auth_token=use_auth_token, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 297, in xisdir
                  raise NotImplementedError("os.path.isdir is not extended to support URLs in streaming mode")
              NotImplementedError: os.path.isdir is not extended to support URLs in streaming mode

Need help to make the dataset viewer work? Open an discussion for direct support.

Dataset Card for DocRED

Dataset Summary

Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs. In order to accelerate the research on document-level RE, we introduce DocRED, a new dataset constructed from Wikipedia and Wikidata with three features: - DocRED annotates both named entities and relations, and is the largest human-annotated dataset for document-level RE from plain text. - DocRED requires reading multiple sentences in a document to extract entities and infer their relations by synthesizing all information of the document. - Along with the human-annotated data, we also offer large-scale distantly supervised data, which enables DocRED to be adopted for both supervised and weakly supervised scenarios.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

Size of downloaded dataset files: 20.03 MB
Size of the generated dataset: 19.19 MB
Total amount of disk used: 39.23 MB

An example of 'train_annotated' looks as follows.

{
    "labels": {
        "evidence": [[0]],
        "head": [0],
        "relation_id": ["P1"],
        "relation_text": ["is_a"],
        "tail": [0]
    },
    "sents": [["This", "is", "a", "sentence"], ["This", "is", "another", "sentence"]],
    "title": "Title of the document",
    "vertexSet": [[{
        "name": "sentence",
        "pos": [3],
        "sent_id": 0,
        "type": "NN"
    }, {
        "name": "sentence",
        "pos": [3],
        "sent_id": 1,
        "type": "NN"
    }], [{
        "name": "This",
        "pos": [0],
        "sent_id": 0,
        "type": "NN"
    }]]
}

Data Fields

The data fields are the same among all splits.

default

title: a string feature.
sents: a dictionary feature containing:
- feature: a string feature.
name: a string feature.
sent_id: a int32 feature.
pos: a list of int32 features.
type: a string feature.
labels: a dictionary feature containing:
- head: a int32 feature.
- tail: a int32 feature.
- relation_id: a string feature.
- relation_text: a string feature.
- evidence: a list of int32 features.

Data Splits

name	train_annotated	train_distant	validation	test
default	3053	101873	998	1000

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@inproceedings{yao2019DocRED,
  title={{DocRED}: A Large-Scale Document-Level Relation Extraction Dataset},
  author={Yao, Yuan and Ye, Deming and Li, Peng and Han, Xu and Lin, Yankai and Liu, Zhenghao and Liu,   Zhiyuan and Huang, Lixin and Zhou, Jie and Sun, Maosong},
  booktitle={Proceedings of ACL 2019},
  year={2019}
}