Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
1K - 10K
ArXiv:
License:
File size: 2,972 Bytes
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---
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](https://arxiv.org/abs/2012.04373).
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
```python
from datasets import load_dataset
dataset = load_dataset("eesuhn/crossner-science")
```
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