hat / README.md
rajenchatterjee's picture
Add HAT dataset: parquet data (train/dev/test, 38 pairs) + card
c12d114 verified
|
Raw
History Blame Contribute Delete
15.5 kB
metadata
license: cc-by-nc-nd-4.0
pretty_name: 'HAT: Hallucination Annotation for Translation'
size_categories:
  - 100K<n<1M
annotations_creators:
  - expert-generated
task_categories:
  - translation
  - text-classification
language:
  - ar
  - nl
  - en
  - fr
  - de
  - hi
  - id
  - it
  - ja
  - ko
  - pl
  - pt
  - ru
  - zh
  - es
  - th
  - tr
  - uk
  - vi
tags:
  - machine-translation
  - hallucination-detection
  - mt-evaluation
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train/*/*.parquet
      - split: validation
        path: data/dev/*/*.parquet
      - split: test
        path: data/test/*/*.parquet
  - config_name: ar_AE-en_US
    data_files:
      - split: train
        path: data/train/ar_AE-en_US/*.parquet
      - split: validation
        path: data/dev/ar_AE-en_US/*.parquet
      - split: test
        path: data/test/ar_AE-en_US/*.parquet
  - config_name: de_DE-en_US
    data_files:
      - split: train
        path: data/train/de_DE-en_US/*.parquet
      - split: validation
        path: data/dev/de_DE-en_US/*.parquet
      - split: test
        path: data/test/de_DE-en_US/*.parquet
  - config_name: en_US-ar_AE
    data_files:
      - split: train
        path: data/train/en_US-ar_AE/*.parquet
      - split: validation
        path: data/dev/en_US-ar_AE/*.parquet
      - split: test
        path: data/test/en_US-ar_AE/*.parquet
  - config_name: en_US-de_DE
    data_files:
      - split: train
        path: data/train/en_US-de_DE/*.parquet
      - split: validation
        path: data/dev/en_US-de_DE/*.parquet
      - split: test
        path: data/test/en_US-de_DE/*.parquet
  - config_name: en_US-es_ES
    data_files:
      - split: train
        path: data/train/en_US-es_ES/*.parquet
      - split: validation
        path: data/dev/en_US-es_ES/*.parquet
      - split: test
        path: data/test/en_US-es_ES/*.parquet
  - config_name: en_US-fr_FR
    data_files:
      - split: train
        path: data/train/en_US-fr_FR/*.parquet
      - split: validation
        path: data/dev/en_US-fr_FR/*.parquet
      - split: test
        path: data/test/en_US-fr_FR/*.parquet
  - config_name: en_US-hi_IN
    data_files:
      - split: train
        path: data/train/en_US-hi_IN/*.parquet
      - split: validation
        path: data/dev/en_US-hi_IN/*.parquet
      - split: test
        path: data/test/en_US-hi_IN/*.parquet
  - config_name: en_US-id_ID
    data_files:
      - split: train
        path: data/train/en_US-id_ID/*.parquet
      - split: validation
        path: data/dev/en_US-id_ID/*.parquet
      - split: test
        path: data/test/en_US-id_ID/*.parquet
  - config_name: en_US-it_IT
    data_files:
      - split: train
        path: data/train/en_US-it_IT/*.parquet
      - split: validation
        path: data/dev/en_US-it_IT/*.parquet
      - split: test
        path: data/test/en_US-it_IT/*.parquet
  - config_name: en_US-ja_JP
    data_files:
      - split: train
        path: data/train/en_US-ja_JP/*.parquet
      - split: validation
        path: data/dev/en_US-ja_JP/*.parquet
      - split: test
        path: data/test/en_US-ja_JP/*.parquet
  - config_name: en_US-ko_KR
    data_files:
      - split: train
        path: data/train/en_US-ko_KR/*.parquet
      - split: validation
        path: data/dev/en_US-ko_KR/*.parquet
      - split: test
        path: data/test/en_US-ko_KR/*.parquet
  - config_name: en_US-nl_NL
    data_files:
      - split: train
        path: data/train/en_US-nl_NL/*.parquet
      - split: validation
        path: data/dev/en_US-nl_NL/*.parquet
      - split: test
        path: data/test/en_US-nl_NL/*.parquet
  - config_name: en_US-pl_PL
    data_files:
      - split: train
        path: data/train/en_US-pl_PL/*.parquet
      - split: validation
        path: data/dev/en_US-pl_PL/*.parquet
      - split: test
        path: data/test/en_US-pl_PL/*.parquet
  - config_name: en_US-pt_BR
    data_files:
      - split: train
        path: data/train/en_US-pt_BR/*.parquet
      - split: validation
        path: data/dev/en_US-pt_BR/*.parquet
      - split: test
        path: data/test/en_US-pt_BR/*.parquet
  - config_name: en_US-ru_RU
    data_files:
      - split: train
        path: data/train/en_US-ru_RU/*.parquet
      - split: validation
        path: data/dev/en_US-ru_RU/*.parquet
      - split: test
        path: data/test/en_US-ru_RU/*.parquet
  - config_name: en_US-th_TH
    data_files:
      - split: train
        path: data/train/en_US-th_TH/*.parquet
      - split: validation
        path: data/dev/en_US-th_TH/*.parquet
      - split: test
        path: data/test/en_US-th_TH/*.parquet
  - config_name: en_US-tr_TR
    data_files:
      - split: train
        path: data/train/en_US-tr_TR/*.parquet
      - split: validation
        path: data/dev/en_US-tr_TR/*.parquet
      - split: test
        path: data/test/en_US-tr_TR/*.parquet
  - config_name: en_US-uk_UA
    data_files:
      - split: train
        path: data/train/en_US-uk_UA/*.parquet
      - split: validation
        path: data/dev/en_US-uk_UA/*.parquet
      - split: test
        path: data/test/en_US-uk_UA/*.parquet
  - config_name: en_US-vi_VN
    data_files:
      - split: train
        path: data/train/en_US-vi_VN/*.parquet
      - split: validation
        path: data/dev/en_US-vi_VN/*.parquet
      - split: test
        path: data/test/en_US-vi_VN/*.parquet
  - config_name: en_US-zh_CN
    data_files:
      - split: train
        path: data/train/en_US-zh_CN/*.parquet
      - split: validation
        path: data/dev/en_US-zh_CN/*.parquet
      - split: test
        path: data/test/en_US-zh_CN/*.parquet
  - config_name: en_US-zh_TW
    data_files:
      - split: train
        path: data/train/en_US-zh_TW/*.parquet
      - split: validation
        path: data/dev/en_US-zh_TW/*.parquet
      - split: test
        path: data/test/en_US-zh_TW/*.parquet
  - config_name: es_ES-en_US
    data_files:
      - split: train
        path: data/train/es_ES-en_US/*.parquet
      - split: validation
        path: data/dev/es_ES-en_US/*.parquet
      - split: test
        path: data/test/es_ES-en_US/*.parquet
  - config_name: fr_FR-en_US
    data_files:
      - split: train
        path: data/train/fr_FR-en_US/*.parquet
      - split: validation
        path: data/dev/fr_FR-en_US/*.parquet
      - split: test
        path: data/test/fr_FR-en_US/*.parquet
  - config_name: hi_IN-en_US
    data_files:
      - split: train
        path: data/train/hi_IN-en_US/*.parquet
      - split: validation
        path: data/dev/hi_IN-en_US/*.parquet
      - split: test
        path: data/test/hi_IN-en_US/*.parquet
  - config_name: id_ID-en_US
    data_files:
      - split: train
        path: data/train/id_ID-en_US/*.parquet
      - split: validation
        path: data/dev/id_ID-en_US/*.parquet
      - split: test
        path: data/test/id_ID-en_US/*.parquet
  - config_name: it_IT-en_US
    data_files:
      - split: train
        path: data/train/it_IT-en_US/*.parquet
      - split: validation
        path: data/dev/it_IT-en_US/*.parquet
      - split: test
        path: data/test/it_IT-en_US/*.parquet
  - config_name: ja_JP-en_US
    data_files:
      - split: train
        path: data/train/ja_JP-en_US/*.parquet
      - split: validation
        path: data/dev/ja_JP-en_US/*.parquet
      - split: test
        path: data/test/ja_JP-en_US/*.parquet
  - config_name: ko_KR-en_US
    data_files:
      - split: train
        path: data/train/ko_KR-en_US/*.parquet
      - split: validation
        path: data/dev/ko_KR-en_US/*.parquet
      - split: test
        path: data/test/ko_KR-en_US/*.parquet
  - config_name: nl_NL-en_US
    data_files:
      - split: train
        path: data/train/nl_NL-en_US/*.parquet
      - split: validation
        path: data/dev/nl_NL-en_US/*.parquet
      - split: test
        path: data/test/nl_NL-en_US/*.parquet
  - config_name: pl_PL-en_US
    data_files:
      - split: train
        path: data/train/pl_PL-en_US/*.parquet
      - split: validation
        path: data/dev/pl_PL-en_US/*.parquet
      - split: test
        path: data/test/pl_PL-en_US/*.parquet
  - config_name: pt_BR-en_US
    data_files:
      - split: train
        path: data/train/pt_BR-en_US/*.parquet
      - split: validation
        path: data/dev/pt_BR-en_US/*.parquet
      - split: test
        path: data/test/pt_BR-en_US/*.parquet
  - config_name: ru_RU-en_US
    data_files:
      - split: train
        path: data/train/ru_RU-en_US/*.parquet
      - split: validation
        path: data/dev/ru_RU-en_US/*.parquet
      - split: test
        path: data/test/ru_RU-en_US/*.parquet
  - config_name: th_TH-en_US
    data_files:
      - split: train
        path: data/train/th_TH-en_US/*.parquet
      - split: validation
        path: data/dev/th_TH-en_US/*.parquet
      - split: test
        path: data/test/th_TH-en_US/*.parquet
  - config_name: tr_TR-en_US
    data_files:
      - split: train
        path: data/train/tr_TR-en_US/*.parquet
      - split: validation
        path: data/dev/tr_TR-en_US/*.parquet
      - split: test
        path: data/test/tr_TR-en_US/*.parquet
  - config_name: uk_UA-en_US
    data_files:
      - split: train
        path: data/train/uk_UA-en_US/*.parquet
      - split: validation
        path: data/dev/uk_UA-en_US/*.parquet
      - split: test
        path: data/test/uk_UA-en_US/*.parquet
  - config_name: vi_VN-en_US
    data_files:
      - split: train
        path: data/train/vi_VN-en_US/*.parquet
      - split: validation
        path: data/dev/vi_VN-en_US/*.parquet
      - split: test
        path: data/test/vi_VN-en_US/*.parquet
  - config_name: zh_CN-en_US
    data_files:
      - split: train
        path: data/train/zh_CN-en_US/*.parquet
      - split: validation
        path: data/dev/zh_CN-en_US/*.parquet
      - split: test
        path: data/test/zh_CN-en_US/*.parquet
  - config_name: zh_TW-en_US
    data_files:
      - split: train
        path: data/train/zh_TW-en_US/*.parquet
      - split: validation
        path: data/dev/zh_TW-en_US/*.parquet
      - split: test
        path: data/test/zh_TW-en_US/*.parquet

HAT: Hallucination Annotation for Translation

🧭 Table of Contents


πŸ“˜ Overview

HAT (Hallucination Annotation for Translation) is a large-scale dataset for hallucination detection in machine translation (MT).
It is released as part of our publication at ACL 2026 (paper).

  • 350,959 span-level annotated samples
  • 38 language pairs
  • ~8,000-10,000 samples per language pair, divided into train, dev, and test sets
  • Annotations by professional translators under strict quality control

HAT enables research on detecting and mitigating hallucinations in MT systems.


πŸš€ Usage

Load the dataset with the πŸ€— datasets library:

from datasets import load_dataset

# All 38 language pairs
ds = load_dataset("apple/hat")
train, validation, test = ds["train"], ds["validation"], ds["test"]

# A single language pair (e.g. English β†’ Japanese)
ds = load_dataset("apple/hat", "en_US-ja_JP")

The available config names are the 38 language pairs (e.g. en_US-ja_JP, fr_FR-en_US); the default config concatenates all pairs. Each config exposes train, validation, and test splits.


βš™οΈ Data Creation Process

The dataset was created through the following steps:

  1. Data Collection:
    Crawled ~5M sentences per language from the web, filtered by language ID, length, and deduplication.

  2. Translation:
    Translated monolingual sentences into target languages using a strong neural MT model.

  3. Sample Selection:
    Selected translations with lower quality (based on quality metrics) to increase the likelihood of hallucinations.

  4. Annotation:
    Professional translators labeled hallucinations under rigorous quality control.

  5. Post-processing:
    Removed samples with issues in source text to ensure data integrity.


πŸ“Š Data Statistics

Split Samples per language pair
Train ~10,000
Dev ~2,000
Test ~3,000

πŸ“‚ Dataset Structure

Datasets are organized in the data/ directory:

data/
β”œβ”€β”€ train/
β”œβ”€β”€ dev/
└── test/

Each split contains subdirectories for each language pair which contains one parquet file.

Split naming: the parquet files live under data/train, data/dev, and data/test. On the Hugging Face Hub the dev files are exposed as the standard validation split, so load_dataset(...) returns train / validation / test.

Schema:

Field Type Description
source_locale string Locale of the source text
source_text string Source sentence
target_locale string Locale of the target text
target_text string Machine-translated output
split string Dataset split (train / dev / test)
label int64 Binary hallucination label (0: no hallucination, 1: contains hallucination)
score float64 Proportion (0–1) of hallucinated characters
annotation string Raw span-level hallucination annotation

πŸ“„ Paper Abstract

Hallucinations in machine translation (MT)β€”outputs that may be fluent yet unfaithful to the source contentβ€”remain a critical obstacle. They hinder the reliable deployment of MT systems in real-world applications. Despite growing attention to this phenomenon, progress has been constrained by the lack of large-scale, high-quality benchmarks dedicated to hallucination detection. We introduce HAT (Hallucination Annotation for Translation), a novel dataset designed to advance research on this problem. HAT comprises 350,959 span-level annotated samples across 38 language pairs, with approximately 8,000–10,000 samples per pair partitioned into training, development, and test sets. Annotations were produced by professional translators under rigorous quality control protocols to ensure reliability. We provide a detailed analysis of hallucination distributions and establish benchmark performance using a diverse set of baselines, including automatic MT evaluation metrics as well as large language models. By providing the first large-scale, systematically annotated resource for hallucination detection in MT, HAT enables the development of more faithful translation models and lays the groundwork for future research on building trustworthy machine translation systems.

πŸ“š Citation

If you use this dataset, please cite:

@inproceedings{chatterjee-etal-2026-hat,
    title = "{HAT}: Hallucination Annotation for Translation",
    author = "Chatterjee, Rajen  and
      Li, Xintong  and
      Charoenpornsawat, Paisarn  and
      Lee, Allen",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.acl-long.721/",
    pages = "15865--15888",
    ISBN = "979-8-89176-390-6",
}

πŸ“„ License

The HAT dataset is licensed under CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/).