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Error code: ConfigNamesError Exception: FileNotFoundError Message: Couldn't find a dataset script at /src/services/worker/seongbo/kodialogbench/kodialogbench.py or any data file in the same directory. Couldn't find 'seongbo/kodialogbench' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/seongbo/kodialogbench@629e92878b2f988fc4ba97e70b68f44f634c0840/dialogue_comprehension/topic/k-sns/test.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip'] Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 79, in compute_config_names_response config_names = get_dataset_config_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1906, in dataset_module_factory raise FileNotFoundError( FileNotFoundError: Couldn't find a dataset script at /src/services/worker/seongbo/kodialogbench/kodialogbench.py or any data file in the same directory. Couldn't find 'seongbo/kodialogbench' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/seongbo/kodialogbench@629e92878b2f988fc4ba97e70b68f44f634c0840/dialogue_comprehension/topic/k-sns/test.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']
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⚠️NOTE: We can't release the datasets originated from AI Hub (K-SNS, K-TDD, K-ED, K-DS) for now, according to the Terms of Use. We're in consultation with the relevant organizations and will make these public in the appropriate form soon.
Dataset Card for KoDialogBench
For most of detailed information, please refer to the following:
- Paper: KoDialogBench: Evaluating Conversational Understanding of Language Models with Korean Dialogue Benchmark
- Repository: GitHub
Dataset Details
Dataset Description
KoDialogBench is a benchmark designed to assess the conversational capabilities of language models in Korean language. To this end, we collected native Korean dialogues on daily topics from public sources (e.g., AI Hub), or translated dialogues from other languages such as English and Chinese. We then structured these conversations into diverse test datasets, spanning from dialogue comprehension to response selection tasks. This benchmark consists of 21 test sets, encompassing various aspects of open-domain colloquial dialogues (e.g., topic, emotion, dialog act).
Data Sources
We collected native Korean dialogues from AI Hub:
- K-SNS stands for Korean SNS (한국어 SNS)
- K-TDD stands for Thematic Daily Dialogues (주제별 텍스트 일상 대화 데이터)
- K-ED stands for Emotional Dialogues (감성 대화 말뭉치)
- K-DS stands for Dialogue Summary (한국어 대화 요약)
We translated public datasets from other languages:
- DailyDialog from "DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset"
- Empathetic Dialogues from "Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset"
- PersonaChat from "Personalizing Dialogue Agents: I have a dog, do you have pets too?"
- SocialDial from "SocialDial: A Benchmark for Socially-Aware Dialogue Systems"
Data Creation
We utilized diverse meta information such as dialogue topic and speaker's emotion which was already annotated in the original datasets to formulate dialogue-related multiple-choice questions. To prevent label imbalance, we sampled the equal number of examples from each class.
Statistics
The dataset has 82,962 examples in total.
Task | Subtask | Source | # Options | # Examples |
---|---|---|---|---|
Dialogue Comprehension | Topic Classification | K-SNS | 6 | 1200 |
Dialogue Comprehension | Topic Classification | K-TDD | 19 | 1900 |
Dialogue Comprehension | Topic Classification | SocialDial | 4 | 400 |
Dialogue Comprehension | Emotion Recognition | K-ED | 6 | 1200 |
Dialogue Comprehension | Emotion Recognition | DailyDialog | 5 | 470 |
Dialogue Comprehension | Emotion Recognition | Empathetic Dialogues | 2 | 2000 |
Dialogue Comprehension | Relation Classification | SocialDial (Distance) | 4 | 524 |
Dialogue Comprehension | Relation Classification | SocialDial (Relation) | 3 | 330 |
Dialogue Comprehension | Location Classification | SocialDial | 4 | 376 |
Dialogue Comprehension | Dialog Act Classification | K-TDD | 4 | 520 |
Dialogue Comprehension | Dialog Act Classification | DailyDialog | 4 | 1000 |
Dialogue Comprehension | Fact Identification | K-DS | 4 | 1200 |
Dialogue Comprehension | Fact Identification | PersonaChat | 4 | 1000 |
Dialogue Comprehension | Fact Identification | Empathetic Dialogues | 4 | 2394 |
Response Selection | K-SNS | 5 | 10295 | |
Response Selection | K-TDD | 5 | 10616 | |
Response Selection | K-ED | 5 | 17818 | |
Response Selection | PersonaChat | 5 | 7801 | |
Response Selection | DailyDialog | 5 | 6740 | |
Response Selection | Empathetic Dialogues | 5 | 7941 | |
Response Selection | SocialDial | 5 | 7237 |
Limitations
Our benchmark may suffer from a chronic problem of benchmark contamination. Due to the scarcity of Korean language resources, there is a possibility that the held-out sources utilized to construct the benchmark might overlap with training data used for some language models.
Ethics Statement
Our benchmark dataset is designed to assess capabilities related to various situations and aspects of conversations in Korean language. To achieve this, we utilized conversational content from publicly available datasets from various sources, either without modification or with translation if necessary. During this process, there is a possibility that harmful content or inappropriate biases existing in the original data may have been conveyed, or may have arisen due to limitations of translation tools. We reject any form of violence, discrimination, or offensive language, and our benchmark dataset and experimental results does not represent such values. If any harmful content or privacy infringement is identified within the dataset, we kindly request immediate notification to the authors. In the event of such cases being reported, we will apply the highest ethical standards and take appropriate actions.
Citation
BibTeX:
@misc{jang2024kodialogbench,
title={KoDialogBench: Evaluating Conversational Understanding of Language Models with Korean Dialogue Benchmark},
author={Seongbo Jang and Seonghyeon Lee and Hwanjo Yu},
year={2024},
eprint={2402.17377},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
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