
# Dataset Card for [naacl2022]

## 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:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

This is a named entity recognition dataset annotated for the science entity recognition task, a [project](https://github.com/neubig/nlp-from-scratch-assignment-2022) from the CMU 11-711 course.

### Supported Tasks and Leaderboards

NER task.

### Languages

English

## Dataset Structure

### Data Instances

A sample of the dataset
{'id': '0',
'tokens': ['We', 'sample', '50', 'negative', 'cases', 'from', 'T5LARGE', '+', 'GenMC', 'for', 'each', 'dataset'],
'ner_tags':['O', 'O', 'O', 'O', 'O', 'O', 'B-MethodName', 'O', 'B-MethodName', 'O', 'O', 'O']}

### Data Fields

id,tokens,ner_tags

- `id`: a `string` feature give the sample index.
- `tokens`: a `list` of `string` features give the sequence.
- `ner_tags`: a `list` of classification labels for each token in the sentence, with possible values including 
`O` (0), `B-MethodName` (1), `I-MethodName` (2), `B-HyperparameterName` (3),`I-HyperparameterName` (4),`B-HyperparameterValue` (5),`I-HyperparameterValue` (6),`B-MetricName` (7),`I-MetricName` (8),`B-MetricValue` (9),`I-MetricValue` (10),`B-TaskName` (11),`I-TaskName` (12),`B-DatasetName` (13),`I-DatasetName` (14).


### Data Splits

Data split into
train.txt
dev.txt
test.txt

## 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

The data is annotated by using labelstudio, the papers are collected from TACL and ACL 2022 conferences.

#### Who are the annotators?

Xiaoyue Cui and Haotian Teng annotated the datasets.

### 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

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

Thanks to [@xcui297](https://github.com/xcui297); [@haotianteng](https://github.com/haotianteng) for adding this dataset.

task_categories:token-classification task_ids:named-entity-recognition annotations_creators:expert-generated language_creators:crowdsourced multilinguality:monolingual size_categories:1K<n<10K source_datasets:original language:en license:afl-3.0 acl sciBERT sci 11711 region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["crowdsourced"], "language": ["en"], "license": ["afl-3.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "pretty_name": "sci_NER_naacl", "tags": ["acl", "sciBERT", "sci", "acl", "11711"]}
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-crowdsourced #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-afl-3.0 #acl #sciBERT #sci #11711 #region-us 


# Dataset Card for [naacl2022]

## 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:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:

### Dataset Summary

This is a named entity recognition dataset annotated for the science entity recognition task, a project from the CMU 11-711 course.

### Supported Tasks and Leaderboards

NER task.

### Languages

English

## Dataset Structure

### Data Instances

A sample of the dataset
{'id': '0',
'tokens': ['We', 'sample', '50', 'negative', 'cases', 'from', 'T5LARGE', '+', 'GenMC', 'for', 'each', 'dataset'],
'ner_tags':['O', 'O', 'O', 'O', 'O', 'O', 'B-MethodName', 'O', 'B-MethodName', 'O', 'O', 'O']}

### Data Fields

id,tokens,ner_tags

- 'id': a 'string' feature give the sample index.
- 'tokens': a 'list' of 'string' features give the sequence.
- 'ner_tags': a 'list' of classification labels for each token in the sentence, with possible values including 
'O' (0), 'B-MethodName' (1), 'I-MethodName' (2), 'B-HyperparameterName' (3),'I-HyperparameterName' (4),'B-HyperparameterValue' (5),'I-HyperparameterValue' (6),'B-MetricName' (7),'I-MetricName' (8),'B-MetricValue' (9),'I-MetricValue' (10),'B-TaskName' (11),'I-TaskName' (12),'B-DatasetName' (13),'I-DatasetName' (14).


### Data Splits

Data split into
URL
URL
URL

## Dataset Creation

### Curation Rationale



### Source Data

#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations

#### Annotation process

The data is annotated by using labelstudio, the papers are collected from TACL and ACL 2022 conferences.

#### Who are the annotators?

Xiaoyue Cui and Haotian Teng annotated the datasets.

### 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







### Contributions

Thanks to @xcui297; @haotianteng for adding this dataset.

# Dataset Card for [naacl2022] ## 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:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact: ### Dataset Summary

This is a named entity recognition dataset annotated for the science entity recognition task, a project from the CMU 11-711 course. ### Supported Tasks and Leaderboards

NER task. ### Languages

English ## Dataset Structure ### Data Instances

A sample of the dataset
{'id': '0',
'tokens': ['We', 'sample', '50', 'negative', 'cases', 'from', 'T5LARGE', '+', 'GenMC', 'for', 'each', 'dataset'],
'ner_tags':['O', 'O', 'O', 'O', 'O', 'O', 'B-MethodName', 'O', 'B-MethodName', 'O', 'O', 'O']} ### Data Fields

id,tokens,ner_tags

- 'id': a 'string' feature give the sample index.
- 'tokens': a 'list' of 'string' features give the sequence.
- 'ner_tags': a 'list' of classification labels for each token in the sentence, with possible values including 
'O' (0), 'B-MethodName' (1), 'I-MethodName' (2), 'B-HyperparameterName' (3),'I-HyperparameterName' (4),'B-HyperparameterValue' (5),'I-HyperparameterValue' (6),'B-MetricName' (7),'I-MetricName' (8),'B-MetricValue' (9),'I-MetricValue' (10),'B-TaskName' (11),'I-TaskName' (12),'B-DatasetName' (13),'I-DatasetName' (14). ### Data Splits

Data split into
URL
URL
URL ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process

The data is annotated by using labelstudio, the papers are collected from TACL and ACL 2022 conferences. #### Who are the annotators?

Xiaoyue Cui and Haotian Teng annotated the datasets. ### 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 ### Contributions

Thanks to @xcui297; @haotianteng for adding this dataset.
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-crowdsourced #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-afl-3.0 #acl #sciBERT #sci #11711 #region-us 
 # Dataset Card for [naacl2022] ## 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:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact: ### Dataset Summary

This is a named entity recognition dataset annotated for the science entity recognition task, a project from the CMU 11-711 course. ### Supported Tasks and Leaderboards

NER task. ### Languages

English ## Dataset Structure ### Data Instances

A sample of the dataset
{'id': '0',
'tokens': ['We', 'sample', '50', 'negative', 'cases', 'from', 'T5LARGE', '+', 'GenMC', 'for', 'each', 'dataset'],
'ner_tags':['O', 'O', 'O', 'O', 'O', 'O', 'B-MethodName', 'O', 'B-MethodName', 'O', 'O', 'O']} ### Data Fields

id,tokens,ner_tags

- 'id': a 'string' feature give the sample index.
- 'tokens': a 'list' of 'string' features give the sequence.
- 'ner_tags': a 'list' of classification labels for each token in the sentence, with possible values including 
'O' (0), 'B-MethodName' (1), 'I-MethodName' (2), 'B-HyperparameterName' (3),'I-HyperparameterName' (4),'B-HyperparameterValue' (5),'I-HyperparameterValue' (6),'B-MetricName' (7),'I-MetricName' (8),'B-MetricValue' (9),'I-MetricValue' (10),'B-TaskName' (11),'I-TaskName' (12),'B-DatasetName' (13),'I-DatasetName' (14). ### Data Splits

Data split into
URL
URL
URL ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process

The data is annotated by using labelstudio, the papers are collected from TACL and ACL 2022 conferences. #### Who are the annotators?

Xiaoyue Cui and Haotian Teng annotated the datasets. ### 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 ### Contributions

Thanks to @xcui297; @haotianteng for adding this dataset.
passage: TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-crowdsourced #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-afl-3.0 #acl #sciBERT #sci #11711 #region-us 
# Dataset Card for [naacl2022]## 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:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:### Dataset Summary

This is a named entity recognition dataset annotated for the science entity recognition task, a project from the CMU 11-711 course.### Supported Tasks and Leaderboards

NER task.### Languages

English## Dataset Structure### Data Instances

A sample of the dataset
{'id': '0',
'tokens': ['We', 'sample', '50', 'negative', 'cases', 'from', 'T5LARGE', '+', 'GenMC', 'for', 'each', 'dataset'],
'ner_tags':['O', 'O', 'O', 'O', 'O', 'O', 'B-MethodName', 'O', 'B-MethodName', 'O', 'O', 'O']}