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|
---
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dataset_info:
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|
- config_name: simplified_ekman
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features:
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|
- name: lt_text
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|
dtype: string
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|
- name: text
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|
dtype: string
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|
- name: labels
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|
dtype:
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|
|
list:
|
|
|
class_label:
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|
names:
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|
|
- admiration
|
|
|
- amusement
|
|
|
- anger
|
|
|
- annoyance
|
|
|
- approval
|
|
|
- caring
|
|
|
- confusion
|
|
|
- curiosity
|
|
|
- desire
|
|
|
- disappointment
|
|
|
- disapproval
|
|
|
- disgust
|
|
|
- embarrassment
|
|
|
- excitement
|
|
|
- fear
|
|
|
- gratitude
|
|
|
- grief
|
|
|
- joy
|
|
|
- love
|
|
|
- nervousness
|
|
|
- optimism
|
|
|
- pride
|
|
|
- realization
|
|
|
- relief
|
|
|
- remorse
|
|
|
- sadness
|
|
|
- surprise
|
|
|
- neutral
|
|
|
- name: labels_ekman
|
|
|
dtype:
|
|
|
list:
|
|
|
class_label:
|
|
|
names:
|
|
|
- anger
|
|
|
- disgust
|
|
|
- fear
|
|
|
- joy
|
|
|
- sadness
|
|
|
- surprise
|
|
|
- neutral
|
|
|
- name: id
|
|
|
dtype: string
|
|
|
splits:
|
|
|
- name: train
|
|
|
num_bytes: 7095238
|
|
|
num_examples: 43410
|
|
|
- name: validation
|
|
|
num_bytes: 885284
|
|
|
num_examples: 5426
|
|
|
- name: test
|
|
|
num_bytes: 882333
|
|
|
num_examples: 5427
|
|
|
download_size: 6057071
|
|
|
dataset_size: 8862855
|
|
|
configs:
|
|
|
- config_name: simplified_ekman
|
|
|
data_files:
|
|
|
- split: train
|
|
|
path: simplified_ekman/train-*
|
|
|
- split: validation
|
|
|
path: simplified_ekman/validation-*
|
|
|
- split: test
|
|
|
path: simplified_ekman/test-*
|
|
|
license: apache-2.0
|
|
|
task_categories:
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|
|
- text-classification
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|
|
language:
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|
|
- lt
|
|
|
- en
|
|
|
---
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|
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|
# Lithuanian GoEmotions dataset
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|
|
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|
|
The original dataset: [GoEmotions](https://huggingface.co/datasets/google-research-datasets/go_emotions) ([paper](https://aclanthology.org/2020.acl-main.372/)).
|
|
|
|
|
|
The derived dataset was machine translated from English into Lithuanian using the free Google Translate API (with [deep-translator](https://pypi.org/project/deep-translator/)). The translation script:
|
|
|
|
|
|
|
|
|
```python
|
|
|
from datasets import load_dataset
|
|
|
from deep_translator import GoogleTranslator
|
|
|
from deep_translator.exceptions import TranslationNotFound
|
|
|
|
|
|
original_dataset = load_dataset("go_emotions", name="simplified")
|
|
|
translator = GoogleTranslator(source="en", target="lt")
|
|
|
|
|
|
def translate_batch(batch):
|
|
|
original_text = batch["text"]
|
|
|
|
|
|
while True:
|
|
|
try:
|
|
|
translated_batch = translator.translate_batch(original_text)
|
|
|
break
|
|
|
except TranslationNotFound:
|
|
|
print(f"Translation failed. Retrying...")
|
|
|
|
|
|
# We fix untranslated entries (None values) by replacing them with the original text
|
|
|
for i in range(len(translated_batch)):
|
|
|
if not translated_batch[i]:
|
|
|
translated_batch[i] = original_text[i]
|
|
|
print(f"Replaced {original_text[i]} vs {translated_batch[i]}")
|
|
|
|
|
|
batch["lt_text"] = translated_batch
|
|
|
|
|
|
return batch
|
|
|
|
|
|
translated_dataset = original_dataset.map(
|
|
|
translate_batch, batched=True, batch_size=500
|
|
|
)
|
|
|
```
|
|
|
|
|
|
The derived dataset uses two aligned tagsets:
|
|
|
|
|
|
- The original 27 + `neutral` emotion labels (may contain more than one label per sample):
|
|
|
```yaml
|
|
|
0: admiration
|
|
|
1: amusement
|
|
|
2: anger
|
|
|
3: annoyance
|
|
|
4: approval
|
|
|
5: caring
|
|
|
6: confusion
|
|
|
7: curiosity
|
|
|
8: desire
|
|
|
9: disappointment
|
|
|
10: disapproval
|
|
|
11: disgust
|
|
|
12: embarrassment
|
|
|
13: excitement
|
|
|
14: fear
|
|
|
15: gratitude
|
|
|
16: grief
|
|
|
17: joy
|
|
|
18: love
|
|
|
19: nervousness
|
|
|
20: optimism
|
|
|
21: pride
|
|
|
22: realization
|
|
|
23: relief
|
|
|
24: remorse
|
|
|
25: sadness
|
|
|
26: surprise
|
|
|
27: neutral
|
|
|
```
|
|
|
|
|
|
- The basic 6 + `neutral` emotion labels as per [Paul Ekman's theory](https://en.wikipedia.org/wiki/Emotion_classification) (may contain more than one label per sample):
|
|
|
```yaml
|
|
|
0: anger
|
|
|
1: disgust
|
|
|
2: fear
|
|
|
3: joy
|
|
|
4: sadness
|
|
|
5: surprise
|
|
|
6: neutral
|
|
|
```
|
|
|
|
|
|
Mapping from the 27 fine-grained emotions to the 6 basic emotions:
|
|
|
|
|
|
| GoEmotions | Ekman |
|
|
|
|---|---|
|
|
|
| admiration | joy |
|
|
|
| amusement | joy |
|
|
|
| anger | anger |
|
|
|
| annoyance | anger |
|
|
|
| approval | joy |
|
|
|
| caring | joy |
|
|
|
| confusion | surprise |
|
|
|
| curiosity | surprise |
|
|
|
| desire | joy |
|
|
|
| disappointment | sadness |
|
|
|
| disapproval | anger |
|
|
|
| disgust | disgust |
|
|
|
| embarrassment | sadness |
|
|
|
| excitement | joy |
|
|
|
| fear | fear |
|
|
|
| gratitude | joy |
|
|
|
| grief | sadness |
|
|
|
| joy | joy |
|
|
|
| love | joy |
|
|
|
| nervousness | fear |
|
|
|
| optimism | joy |
|
|
|
| pride | joy |
|
|
|
| realization | surprise |
|
|
|
| relief | joy |
|
|
|
| remorse | sadness |
|
|
|
| sadness | sadness |
|
|
|
| surprise | surprise |
|
|
|
|
|
|
## Acknowledgements
|
|
|
|
|
|
This work was supported by the EU Recovery and Resilience Facility project [Language Technology Initiative](https://www.vti.lu.lv) (2.3.1.1.i.0/1/22/I/CFLA/002). |
