Datasets:
wnut_17

Languages: English
Multilinguality: monolingual
Size Categories: 1K<n<10K
Language Creators: found
Annotations Creators: crowdsourced
Source Datasets: original
License: cc-by-4.0
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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:    ValueError
Message:      Cannot seek streaming HTTP file
Traceback:    Traceback (most recent call last):
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 485, in compute_first_rows_response
                  rows = get_rows(
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 120, in decorator
                  return func(*args, **kwargs)
                File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 164, in get_rows
                  ds = load_dataset(
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/load.py", line 1751, in load_dataset
                  return builder_instance.as_streaming_dataset(split=split)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1206, in as_streaming_dataset
                  splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
                File "/tmp/modules-cache/datasets_modules/datasets/wnut_17/077c7f08b8dbc800692e8c9186cdf3606d5849ab0e7be662e6135bb10eba54f9/wnut_17.py", line 131, in _split_generators
                  downloaded_files = dl_manager.download_and_extract(urls_to_download)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1074, in download_and_extract
                  return self.extract(self.download(url_or_urls))
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1026, in extract
                  urlpaths = map_nested(self._extract, url_or_urls, map_tuple=True)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 444, in map_nested
                  mapped = [
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 445, in <listcomp>
                  _single_map_nested((function, obj, types, None, True, None))
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 346, in _single_map_nested
                  return function(data_struct)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1031, in _extract
                  protocol = _get_extraction_protocol(urlpath, use_auth_token=self.download_config.use_auth_token)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 434, in _get_extraction_protocol
                  return _get_extraction_protocol_with_magic_number(f)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 401, in _get_extraction_protocol_with_magic_number
                  f.seek(0)
                File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 737, in seek
                  raise ValueError("Cannot seek streaming HTTP file")
              ValueError: Cannot seek streaming HTTP file

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Dataset Card for "wnut_17"

Dataset Summary

WNUT 17: Emerging and Rare entity recognition

This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions. Named entities form the basis of many modern approaches to other tasks (like event clustering and summarisation), but recall on them is a real problem in noisy text - even among annotators. This drop tends to be due to novel entities and surface forms. Take for example the tweet “so.. kktny in 30 mins?” - even human experts find entity kktny hard to detect and resolve. This task will evaluate the ability to detect and classify novel, emerging, singleton named entities in noisy text.

The goal of this task is to provide a definition of emerging and of rare entities, and based on that, also datasets for detecting these entities.

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

  • Size of downloaded dataset files: 0.76 MB
  • Size of the generated dataset: 1.66 MB
  • Total amount of disk used: 2.43 MB

An example of 'train' looks as follows.

{
    "id": "0",
    "ner_tags": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0],
    "tokens": ["@paulwalk", "It", "'s", "the", "view", "from", "where", "I", "'m", "living", "for", "two", "weeks", ".", "Empire", "State", "Building", "=", "ESB", ".", "Pretty", "bad", "storm", "here", "last", "evening", "."]
}

Data Fields

The data fields are the same among all splits:

  • id (string): ID of the example.
  • tokens (list of string): Tokens of the example text.
  • ner_tags (list of class labels): NER tags of the tokens (using IOB2 format), with possible values:
    • 0: O
    • 1: B-corporation
    • 2: I-corporation
    • 3: B-creative-work
    • 4: I-creative-work
    • 5: B-group
    • 6: I-group
    • 7: B-location
    • 8: I-location
    • 9: B-person
    • 10: I-person
    • 11: B-product
    • 12: I-product

Data Splits

train validation test
3394 1009 1287

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@inproceedings{derczynski-etal-2017-results,
    title = "Results of the {WNUT}2017 Shared Task on Novel and Emerging Entity Recognition",
    author = "Derczynski, Leon  and
      Nichols, Eric  and
      van Erp, Marieke  and
      Limsopatham, Nut",
    booktitle = "Proceedings of the 3rd Workshop on Noisy User-generated Text",
    month = sep,
    year = "2017",
    address = "Copenhagen, Denmark",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-4418",
    doi = "10.18653/v1/W17-4418",
    pages = "140--147",
    abstract = "This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions.
                Named entities form the basis of many modern approaches to other tasks (like event clustering and summarization),
                but recall on them is a real problem in noisy text - even among annotators.
                This drop tends to be due to novel entities and surface forms.
                Take for example the tweet {``}so.. kktny in 30 mins?!{''} {--} even human experts find the entity {`}kktny{'}
                hard to detect and resolve. The goal of this task is to provide a definition of emerging and of rare entities,
                and based on that, also datasets for detecting these entities. The task as described in this paper evaluated the
                ability of participating entries to detect and classify novel and emerging named entities in noisy text.",
}

Contributions

Thanks to @thomwolf, @lhoestq, @stefan-it, @lewtun, @jplu for adding this dataset.

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