Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
1K - 10K
License:
File size: 3,874 Bytes
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---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- crowdsourced
license:
- afl-3.0
multilinguality:
- monolingual
pretty_name: sci_NER_naacl
size_categories:
- 1K<n<10K
source_datasets:
- original
tags:
- acl
- sciBERT
- sci
- acl
- '11711'
task_categories:
- token-classification
task_ids:
- named-entity-recognition
---
# 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.
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