README.md

metadata

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
• 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 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; @haotianteng for adding this dataset.