
# Dataset Card for ontonotes_english

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [CoNLL-2012 Shared Task](https://conll.cemantix.org/2012/data.html), [Author's page](https://cemantix.org/data/ontonotes.html)
- **Repository:**
- **Paper:** [Towards Robust Linguistic Analysis using OntoNotes](https://aclanthology.org/W13-3516/)
- **Leaderboard:** [Papers With Code](https://paperswithcode.com/sota/named-entity-recognition-ner-on-ontonotes-v5)
- **Point of Contact:**

### Dataset Summary

This is preprocessed version of what I assume is OntoNotes v5.0.

Instead of having sentences stored in files, files are unpacked and sentences are the rows now. Also, fields were renamed in order to match [conll2003](https://huggingface.co/datasets/conll2003).

The source of data is from private repository, which in turn got data from another public repository, location of which is unknown :)

Since data from all repositories had no license (creator of the private repository told me so), there should be no licensing issues. But bear in mind, I don't give any guarantees that this is real OntoNotes, and may differ as a result.

### Supported Tasks and Leaderboards

- [Named Entity Recognition on Ontonotes v5 (English)](https://paperswithcode.com/sota/named-entity-recognition-ner-on-ontonotes-v5)
- [Coreference Resolution on OntoNotes](https://paperswithcode.com/sota/coreference-resolution-on-ontonotes)
- [Semantic Role Labeling on OntoNotes](https://paperswithcode.com/sota/semantic-role-labeling-on-ontonotes)

### Languages

English

## Dataset Structure

### Data Instances

```
{
    'tokens': ['Well', ',', 'the', 'Hundred', 'Regiments', 'Offensive', 'was', 'divided', 'into', 'three', 'phases', '.'],
    'ner_tags': [0, 0, 29, 30, 30, 30, 0, 0, 0, 27, 0, 0]
}
```

### Data Fields

- **`tokens`** (*`List[str]`*) : **`words`** in original dataset
- **`ner_tags`** (*`List[ClassLabel]`*) : **`named_entities`** in original dataset. The BIO tags for named entities in the sentence. 
  - tag set : `datasets.ClassLabel(num_classes=37, names=["O", "B-PERSON", "I-PERSON", "B-NORP", "I-NORP", "B-FAC", "I-FAC", "B-ORG", "I-ORG", "B-GPE", "I-GPE", "B-LOC", "I-LOC", "B-PRODUCT", "I-PRODUCT", "B-DATE", "I-DATE", "B-TIME", "I-TIME", "B-PERCENT", "I-PERCENT", "B-MONEY", "I-MONEY", "B-QUANTITY", "I-QUANTITY", "B-ORDINAL", "I-ORDINAL", "B-CARDINAL", "I-CARDINAL", "B-EVENT", "I-EVENT", "B-WORK_OF_ART", "I-WORK_OF_ART", "B-LAW", "I-LAW", "B-LANGUAGE", "I-LANGUAGE",])`

### Data Splits

_train_, _validation_, and _test_

## 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

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## 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

No license

### Citation Information

```
@inproceedings{pradhan-etal-2013-towards,
    title = "Towards Robust Linguistic Analysis using {O}nto{N}otes",
    author = {Pradhan, Sameer  and
      Moschitti, Alessandro  and
      Xue, Nianwen  and
      Ng, Hwee Tou  and
      Bj{\"o}rkelund, Anders  and
      Uryupina, Olga  and
      Zhang, Yuchen  and
      Zhong, Zhi},
    booktitle = "Proceedings of the Seventeenth Conference on Computational Natural Language Learning",
    month = aug,
    year = "2013",
    address = "Sofia, Bulgaria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W13-3516",
    pages = "143--152",
}
```

### Contributions

Thanks to the author of private repository, that uploaded this dataset.
task_categories:token-classification task_ids:named-entity-recognition annotations_creators:found language_creators:found multilinguality:monolingual size_categories:10K<n<100K source_datasets:extended|other language:en license:unknown region:us
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["extended|other"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "pretty_name": "ontonotes_english"}
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-extended|other #language-English #license-unknown #region-us 


# Dataset Card for ontonotes_english

## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

## Dataset Description

- Homepage: CoNLL-2012 Shared Task, Author's page
- Repository:
- Paper: Towards Robust Linguistic Analysis using OntoNotes
- Leaderboard: Papers With Code
- Point of Contact:

### Dataset Summary

This is preprocessed version of what I assume is OntoNotes v5.0.

Instead of having sentences stored in files, files are unpacked and sentences are the rows now. Also, fields were renamed in order to match conll2003.

The source of data is from private repository, which in turn got data from another public repository, location of which is unknown :)

Since data from all repositories had no license (creator of the private repository told me so), there should be no licensing issues. But bear in mind, I don't give any guarantees that this is real OntoNotes, and may differ as a result.

### Supported Tasks and Leaderboards

- Named Entity Recognition on Ontonotes v5 (English)
- Coreference Resolution on OntoNotes
- Semantic Role Labeling on OntoNotes

### Languages

English

## Dataset Structure

### Data Instances



### Data Fields

- 'tokens' (*'List[str]'*) : 'words' in original dataset
- 'ner_tags' (*'List[ClassLabel]'*) : 'named_entities' in original dataset. The BIO tags for named entities in the sentence. 
  - tag set : 'datasets.ClassLabel(num_classes=37, names=["O", "B-PERSON", "I-PERSON", "B-NORP", "I-NORP", "B-FAC", "I-FAC", "B-ORG", "I-ORG", "B-GPE", "I-GPE", "B-LOC", "I-LOC", "B-PRODUCT", "I-PRODUCT", "B-DATE", "I-DATE", "B-TIME", "I-TIME", "B-PERCENT", "I-PERCENT", "B-MONEY", "I-MONEY", "B-QUANTITY", "I-QUANTITY", "B-ORDINAL", "I-ORDINAL", "B-CARDINAL", "I-CARDINAL", "B-EVENT", "I-EVENT", "B-WORK_OF_ART", "I-WORK_OF_ART", "B-LAW", "I-LAW", "B-LANGUAGE", "I-LANGUAGE",])'

### Data Splits

_train_, _validation_, and _test_

## Dataset Creation

### Curation Rationale



### Source Data

#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations

#### Annotation process



#### Who are the annotators?



### Personal and Sensitive Information



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information

No license





### Contributions

Thanks to the author of private repository, that uploaded this dataset.
# Dataset Card for ontonotes_english ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: CoNLL-2012 Shared Task, Author's page
- Repository:
- Paper: Towards Robust Linguistic Analysis using OntoNotes
- Leaderboard: Papers With Code
- Point of Contact: ### Dataset Summary

This is preprocessed version of what I assume is OntoNotes v5.0.

Instead of having sentences stored in files, files are unpacked and sentences are the rows now. Also, fields were renamed in order to match conll2003.

The source of data is from private repository, which in turn got data from another public repository, location of which is unknown :)

Since data from all repositories had no license (creator of the private repository told me so), there should be no licensing issues. But bear in mind, I don't give any guarantees that this is real OntoNotes, and may differ as a result. ### Supported Tasks and Leaderboards

- Named Entity Recognition on Ontonotes v5 (English)
- Coreference Resolution on OntoNotes
- Semantic Role Labeling on OntoNotes ### Languages

English ## Dataset Structure ### Data Instances ### Data Fields

- 'tokens' (*'List[str]'*) : 'words' in original dataset
- 'ner_tags' (*'List[ClassLabel]'*) : 'named_entities' in original dataset. The BIO tags for named entities in the sentence. 
  - tag set : 'datasets.ClassLabel(num_classes=37, names=["O", "B-PERSON", "I-PERSON", "B-NORP", "I-NORP", "B-FAC", "I-FAC", "B-ORG", "I-ORG", "B-GPE", "I-GPE", "B-LOC", "I-LOC", "B-PRODUCT", "I-PRODUCT", "B-DATE", "I-DATE", "B-TIME", "I-TIME", "B-PERCENT", "I-PERCENT", "B-MONEY", "I-MONEY", "B-QUANTITY", "I-QUANTITY", "B-ORDINAL", "I-ORDINAL", "B-CARDINAL", "I-CARDINAL", "B-EVENT", "I-EVENT", "B-WORK_OF_ART", "I-WORK_OF_ART", "B-LAW", "I-LAW", "B-LANGUAGE", "I-LANGUAGE",])' ### Data Splits

_train_, _validation_, and _test_ ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

No license ### Contributions

Thanks to the author of private repository, that uploaded this dataset.
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-extended|other #language-English #license-unknown #region-us 
 # Dataset Card for ontonotes_english ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: CoNLL-2012 Shared Task, Author's page
- Repository:
- Paper: Towards Robust Linguistic Analysis using OntoNotes
- Leaderboard: Papers With Code
- Point of Contact: ### Dataset Summary

This is preprocessed version of what I assume is OntoNotes v5.0.

Instead of having sentences stored in files, files are unpacked and sentences are the rows now. Also, fields were renamed in order to match conll2003.

The source of data is from private repository, which in turn got data from another public repository, location of which is unknown :)

Since data from all repositories had no license (creator of the private repository told me so), there should be no licensing issues. But bear in mind, I don't give any guarantees that this is real OntoNotes, and may differ as a result. ### Supported Tasks and Leaderboards

- Named Entity Recognition on Ontonotes v5 (English)
- Coreference Resolution on OntoNotes
- Semantic Role Labeling on OntoNotes ### Languages

English ## Dataset Structure ### Data Instances ### Data Fields

- 'tokens' (*'List[str]'*) : 'words' in original dataset
- 'ner_tags' (*'List[ClassLabel]'*) : 'named_entities' in original dataset. The BIO tags for named entities in the sentence. 
  - tag set : 'datasets.ClassLabel(num_classes=37, names=["O", "B-PERSON", "I-PERSON", "B-NORP", "I-NORP", "B-FAC", "I-FAC", "B-ORG", "I-ORG", "B-GPE", "I-GPE", "B-LOC", "I-LOC", "B-PRODUCT", "I-PRODUCT", "B-DATE", "I-DATE", "B-TIME", "I-TIME", "B-PERCENT", "I-PERCENT", "B-MONEY", "I-MONEY", "B-QUANTITY", "I-QUANTITY", "B-ORDINAL", "I-ORDINAL", "B-CARDINAL", "I-CARDINAL", "B-EVENT", "I-EVENT", "B-WORK_OF_ART", "I-WORK_OF_ART", "B-LAW", "I-LAW", "B-LANGUAGE", "I-LANGUAGE",])' ### Data Splits

_train_, _validation_, and _test_ ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

No license ### Contributions

Thanks to the author of private repository, that uploaded this dataset.