Datasets:
Tasks:
Token Classification
Languages:
Slovenian
Size:
1K - 10K
Tags:
metaphor-classification
metonymy-classification
metaphor-frame-classification
multiword-expression-detection
License:
annotations_creators: | |
- expert-generated | |
language_creators: | |
- found | |
language: | |
- sl | |
license: | |
- cc-by-nc-sa-4.0 | |
multilinguality: | |
- monolingual | |
size_categories: | |
- 1K<n<10K | |
source_datasets: [] | |
task_categories: | |
- token-classification | |
task_ids: [] | |
pretty_name: G-KOMET | |
tags: | |
- metaphor-classification | |
- metonymy-classification | |
- metaphor-frame-classification | |
- multiword-expression-detection | |
# Dataset Card for G-KOMET | |
### Dataset Summary | |
G-KOMET 1.0 is a corpus of metaphorical expressions in spoken Slovene language, covering around 50,000 lexical units across 5695 sentences. The corpus contains samples from the Gos corpus of spoken Slovene and includes a balanced set of transcriptions of informative, educational, entertaining, private, and public discourse. | |
It is also annotated with idioms and metonymies. Note that these are both annotated as metaphor types. This is different from the annotations in [KOMET](https://huggingface.co/datasets/cjvt/komet), where these are both considered a type of frame. We keep the data as untouched as possible and let the user decide how they want to handle this. | |
### Supported Tasks and Leaderboards | |
Metaphor detection, metonymy detection, metaphor type classification, metaphor frame classification. | |
### Languages | |
Slovenian. | |
## Dataset Structure | |
### Data Instances | |
A sample instance from the dataset: | |
``` | |
{ | |
'document_name': 'G-Komet001.xml', | |
'idx': 3, | |
'idx_paragraph': 0, | |
'idx_sentence': 3, | |
'sentence_words': ['no', 'zdaj', 'samo', 'še', 'za', 'eno', 'orientacijo'], | |
'met_type': [ | |
{'type': 'MRWi', 'word_indices': [6]} | |
], | |
'met_frame': [ | |
{'type': 'spatial_orientation', 'word_indices': [6]} | |
] | |
} | |
``` | |
The sentence comes from the document `G-Komet001.xml`, is the 3rd sentence in the document and is the 3rd sentence inside the 0th paragraph in the document. | |
The word "orientacijo" is annotated as an indirect metaphor-related word (`MRWi`). | |
It is also annotated with the frame "spatial_orientation". | |
### Data Fields | |
- `document_name`: a string containing the name of the document in which the sentence appears; | |
- `idx`: a uint32 containing the index of the sentence inside its document; | |
- `idx_paragraph`: a uint32 containing the index of the paragraph in which the sentence appears; | |
- `idx_sentence`: a uint32 containing the index of the sentence inside its paragraph; | |
containing the consecutive number of the paragraph inside the current news article; | |
- `sentence_words`: words in the sentence; | |
- `met_type`: metaphors in the sentence, marked by their type and word indices; | |
- `met_frame`: metaphor frames in the sentence, marked by their type (frame name) and word indices. | |
## Dataset Creation | |
The corpus contains samples from the GOS corpus of spoken Slovene and includes a balanced set of transcriptions of informative, educational, entertaining, private, and public discourse. It contains hand-annotated metaphor-related words, i.e. linguistic expressions that have the potential for people to interpret them as metaphors, idioms, i.e. multi-word units in which at least one word has been used metaphorically, and metonymies, expressions that we use to express something else. | |
For more information, please check out the paper (which is in Slovenian language) or contact the dataset author. | |
## Additional Information | |
### Dataset Curators | |
Špela Antloga. | |
### Licensing Information | |
CC BY-NC-SA 4.0 | |
### Citation Information | |
``` | |
@InProceedings{antloga2022gkomet, | |
title = {Korpusni pristopi za identifikacijo metafore in metonimije: primer metonimije v korpusu gKOMET}, | |
author={Antloga, \v{S}pela}, | |
booktitle={Proceedings of the Conference on Language Technologies and Digital Humanities (Student papers)}, | |
year={2022}, | |
pages={271-277} | |
} | |
``` | |
### Contributions | |
Thanks to [@matejklemen](https://github.com/matejklemen) for adding this dataset. | |