ChindaMT-BroadEval

Paper: Reference-Grounded Data Curation for Instruction-Following Thai-English Machine Translation, AACL-IJCNLP 2026 Main Conference

800 sample English-Thai evaluation set across 10 broader domains, extending CoreEval with news, literary, social, and speech content (about 25% paragraph-length inputs). Cross-domain generalization suite for the ChindaMT model family.

• plain split: 400 plain-translation samples (200 en-to-th + 200 th-to-en).
• constrained split: 400 separate samples (200 en-to-th + 200 th-to-en) with a Rules: block of 1–4 rules drawn from 5 constraint categories (content, numerical, stylistic, format, linguistic).

Each row carries the source text, the formatted instruction, and pre-generated predictions from ChindaMT-4B, ChindaMT-2B, and ChindaMT-0.8B. No reference translation is shipped; the suite is designed for pairwise LLM-judge or human evaluation.

Dataset structure

Each row in plain.jsonl and constrained.jsonl has the following fields:

Field	Type	Description
id	string	Unique row identifier
direction	string	en->th or th->en
domain	string	One of news, literary, social, speech, legal, plus CoreEval domains
context_type	string	sentence or paragraph
source_dataset	string	Provenance
source_license	string	License of the source row (apache-2.0, or cc-by-nc-4.0 for one row)
source_locator	string	Provenance pointer
source_text	string	The raw source text
instruction	string	Formatted prompt fed to the model
phenomena_tags	list[string]	Optional content tags (e.g., has_latin)
rules	list[string]	Constraint rules (constrained split only)
verifiable_checks	list[object]	Optional machine-checkable rule checks, each with a type and a value (constrained split only)
split	string	plain or constrained
prediction_chindamt_4b	string	Output from ChindaMT-4B
prediction_chindamt_2b	string	Output from ChindaMT-2B
prediction_chindamt_08b	string	Output from ChindaMT-0.8B

Loading

from datasets import load_dataset

plain = load_dataset("iapp/ChindaMT-BroadEval", "plain", split="train")
constrained = load_dataset("iapp/ChindaMT-BroadEval", "constrained", split="train")

Provenance

Source	Rows	Source license
WMT24++ en-th (google/wmt24pp)	462	Apache-2.0
Suraponn/thai_instruction_sft	337	Apache-2.0
airesearch/WangchanThaiInstruct (row Legal_9579)	1	CC-BY-NC-4.0

BroadEval is curated independently of the ChindaMT training pool. Item plain-th2en-0178 is the only row from WangchanThaiInstruct and carries that source's CC-BY-NC-4.0 terms in its source_license field.

Citation

@misc{chayintr2026rgdc,
  title         = {Reference-Grounded Data Curation for Instruction-Following Thai-English Machine Translation},
  author        = {Chay-intr, Thodsaporn and Harnchang, Krittapad and Thabua, Mahannop and Viriyayudhakorn, Kobkrit and Theeramunkong, Thanaruk},
  year          = {2026},
  eprint        = {2609.34770},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CL},
  url           = {https://arxiv.org/abs/2609.34770},
  note          = {Accepted at AACL-IJCNLP 2026 (Main Conference)}
}

License

Released under CC-BY-SA 4.0 as a whole. Each row carries its source license in source_license, and the terms of that field apply to the row; the one CC-BY-NC-4.0 row may not be used commercially. When using this dataset, please credit the ChindaMT project and license any derivatives under CC-BY-SA 4.0.

iApp AI Research