README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
language:
  - en
license:
  - other
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - token-classification
task_ids:
  - named-entity-recognition
paperswithcode_id: crossner
pretty_name: CrossNER-SCIENCE
dataset_info:
  features:
    - name: tokens
      sequence: string
    - name: ner_tags
      sequence:
        class_label:
          names:
            '0': O
            '1': B-scientist
            '2': I-scientist
            '3': B-person
            '4': I-person
            '5': B-university
            '6': I-university
            '7': B-organisation
            '8': I-organisation
            '9': B-country
            '10': I-country
            '11': B-location
            '12': I-location
            '13': B-discipline
            '14': I-discipline
            '15': B-enzyme
            '16': I-enzyme
            '17': B-protein
            '18': I-protein
            '19': B-chemicalelement
            '20': I-chemicalelement
            '21': B-chemicalcompound
            '22': I-chemicalcompound
            '23': B-astronomicalobject
            '24': I-astronomicalobject
            '25': B-academicjournal
            '26': I-academicjournal
            '27': B-event
            '28': I-event
            '29': B-theory
            '30': I-theory
            '31': B-award
            '32': I-award
            '33': B-misc
            '34': I-misc
  splits:
    - name: train
      num_bytes: 20000
      num_examples: 200
    - name: validation
      num_bytes: 45000
      num_examples: 450
    - name: test
      num_bytes: 54300
      num_examples: 543

CrossNER SCIENCE Dataset

An NER dataset for cross-domain evaluation, read more.
This split contains labeled data from the SCIENCE domain.

Features

• tokens: A list of words in the sentence
• ner_tags: A list of NER labels (as integers) corresponding to each token

Label Mapping

The dataset uses the following 35 labels:

Index	Label
0	O
1	B-scientist
2	I-scientist
3	B-person
4	I-person
5	B-university
6	I-university
7	B-organisation
8	I-organisation
9	B-country
10	I-country
11	B-location
12	I-location
13	B-discipline
14	I-discipline
15	B-enzyme
16	I-enzyme
17	B-protein
18	I-protein
19	B-chemicalelement
20	I-chemicalelement
21	B-chemicalcompound
22	I-chemicalcompound
23	B-astronomicalobject
24	I-astronomicalobject
25	B-academicjournal
26	I-academicjournal
27	B-event
28	I-event
29	B-theory
30	I-theory
31	B-award
32	I-award
33	B-misc
34	I-misc

Usage

from datasets import load_dataset

dataset = load_dataset("eesuhn/crossner-science")