Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
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Sub-tasks:
named-entity-recognition
Languages:
English
Size:
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Dataset Viewer
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End of preview. Expand
in Data Studio
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")
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