Datasets:

IndexTeam
/

NAtIveLong

---
pretty_name: NAtIveLong Long-Document Translation Benchmark
license: other
license_name: component-specific-upstream-terms
license_link: https://github.com/EleanorJiang/BlonDe/blob/main/TERMS_OF_USE
language: [zh, en]
task_categories: [translation]
size_categories: [n<1K]
tags: [benchmark, evaluation, long-document, literary-translation]
configs:
  - config_name: bwb_metadata
    data_files:
      - split: test
        path: bwb/case-index.jsonl
  - config_name: guofeng_metadata
    data_files:
      - split: test
        path: guofeng/case-index.jsonl
---
# NAtIveLong

NAtIveLong evaluates Chinese-to-English long-document translation at 4K, 8K,
16K, 32K and 64K source-token bands. It defines **84 BWB cases and 84 GuoFeng
cases**, using six held-out books per corpus from the upstream training corpora.
These are project-defined splits, not the upstream official test splits.

## What this release contains

**This public release contains metadata, reconstruction information and evaluation
code. It contains no BWB or GuoFeng source books or reference translations.**

| Corpus | 4K | 8K | 16K | 32K | 64K | Total | Public delivery |
|---|---:|---:|---:|---:|---:|---:|---|
| BWB | 24 | 24 | 12 | 12 | 12 | 84 | Case index, book/chapter mapping, frozen prompt and provenance |
| GuoFeng | 24 | 24 | 12 | 12 | 12 | 84 | Case index, numerical extraction recipe and reconstruction script |

```python
from datasets import load_dataset
bwb = load_dataset("IndexTeam/NAtIveLong", "bwb_metadata", split="test")
guofeng = load_dataset("IndexTeam/NAtIveLong", "guofeng_metadata", split="test")
assert len(bwb) == len(guofeng) == 84
```

The dataset viewer shows case metadata; it does not supply translation inputs.
Do not use references, expected hashes or scoring metadata as model inputs.

## Obtain official data

For BWB, obtain the official Train corpus from the
[BWB download](https://drive.google.com/drive/folders/12K1-DWmpEdqkaR_61aogdywsALDg4z1L)
and follow its [terms](https://github.com/EleanorJiang/BlonDe/blob/main/TERMS_OF_USE).
The released `bwb/chapter-map.jsonl` maps project-ordered chapters to physical
upstream records, and `bwb/case-index.jsonl` provides frozen endpoints and hashes.
This release does not include an automated BWB text reconstruction utility.
See [BWB details](bwb/README.md) for the mapping and scoring input requirements.

For GuoFeng, obtain **V1 Train** through the
[official registration form](https://forms.gle/YqJPkfLgGmACbnbU6), then run:

```bash
python guofeng/reconstruct.py --source raw/train.zh --reference raw/train.en \
  --output reconstructed/guofeng
```

The standard-library script verifies official input hashes and all 168
reconstructed source/reference hashes. The output directory must be new.
See [GuoFeng details](guofeng/README.md). Reconstructed text is local material,
subject to the upstream terms, and is not included in this public dataset.

## Generate and evaluate

The [evaluation guide](evaluation/README.md) documents prediction formats,
installation, fixed scoring models and a two-document synthetic example.
Use the frozen `zh-en-document-v3` prompt and save each final translation with
its `case_id`. Record the inference engine, model revision, reasoning setting,
output limit and finish reason. The 64K band describes Chinese source length;
reserve sufficient output and total-context budget for its English translation.

The primary score is **SEGALE-COMET**, using `summary.json` →
`five_band_macro.value`: an equal-weight mean over the five length bands.
Report BWB and GuoFeng separately, plus scored/total case coverage. Scores are
on a 0–1 scale; chrF2 is auxiliary. Incomplete bands do not produce a valid full
five-band score. Evaluation code includes upstream notices and licenses.

## Limitations and provenance

Length labels use the frozen tokenizer with 5% tolerance. Windows overlap within
books, and these tests have been used in model development and comparison.
GuoFeng reconstruction preserves the existing `undefined` row in two 127-dylr
cases; it does not silently repair the frozen benchmark.

`release_manifest.json` records the source revision and public file hashes.
`SHA256SUMS` checks the delivered files. The original BWB text archive was
intentionally excluded from this public release; BWB's metadata describes the
original frozen data, not newly reselected examples.

## Attribution and terms

- [BWB / BlonDe](https://github.com/EleanorJiang/BlonDe): upstream source and
  [terms of use](https://github.com/EleanorJiang/BlonDe/blob/main/TERMS_OF_USE).
- [GuoFeng](https://github.com/longyuewangdcu/GuoFeng-Webnovel): upstream source,
  non-commercial research and redistribution conditions.
- [SEGALE](https://github.com/NVlabs/SEGALE): component notices are in
  `evaluation/NOTICE.md` and the vendored directories.
- Model family: [Index-Translate](https://github.com/bilibili/Index-Translate).

We grant no additional rights in underlying books or translations. The evaluation
code is Apache-2.0 under `evaluation/LICENSE`; upstream corpus terms apply
separately. See [LICENSE.md](LICENSE.md).

## Citation

If you use this benchmark, please cite the [Index-Translate technical report](https://arxiv.org/abs/2609.40181):

```bibtex
@techreport{indextranslate2026,
  author={Tianjiao Li and Mengran Yu and Chenyu Shi and Lusheng Zhang and
          Qisi Chen and Yanshan Zhou and Ji Qi and Jingying Liu and
          Yuang Feng and Ziang Cui and Tianxing Yan},
  title={Index-Translate: A Multilingual Translation Model Family --- Text, Speech, Controlled Dubbing, and Long-Document Translation},
  institution={Index LLM Team},
  year={2026},
  month={September},
  eprint={2609.40181},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2609.40181}
}
```

## Benchmark collection

Part of the [Index-Translate Benchmarks collection](https://huggingface.co/collections/IndexTeam/index-translate-benchmarks-6ac16fee5057f40abd7d31b7).

	---
	pretty_name: NAtIveLong Long-Document Translation Benchmark
	license: other
	license_name: component-specific-upstream-terms
	license_link: https://github.com/EleanorJiang/BlonDe/blob/main/TERMS_OF_USE
	language: [zh, en]
	task_categories: [translation]
	size_categories: [n<1K]
	tags: [benchmark, evaluation, long-document, literary-translation]
	configs:
	- config_name: bwb_metadata
	data_files:
	- split: test
	path: bwb/case-index.jsonl
	- config_name: guofeng_metadata
	data_files:
	- split: test
	path: guofeng/case-index.jsonl
	---

	# NAtIveLong

	NAtIveLong evaluates Chinese-to-English long-document translation at 4K, 8K,
	16K, 32K and 64K source-token bands. It defines **84 BWB cases and 84 GuoFeng
	cases**, using six held-out books per corpus from the upstream training corpora.
	These are project-defined splits, not the upstream official test splits.

	## What this release contains

	**This public release contains metadata, reconstruction information and evaluation
	code. It contains no BWB or GuoFeng source books or reference translations.**

	\| Corpus \| 4K \| 8K \| 16K \| 32K \| 64K \| Total \| Public delivery \|
	\|---\|---:\|---:\|---:\|---:\|---:\|---:\|---\|
	\| BWB \| 24 \| 24 \| 12 \| 12 \| 12 \| 84 \| Case index, book/chapter mapping, frozen prompt and provenance \|
	\| GuoFeng \| 24 \| 24 \| 12 \| 12 \| 12 \| 84 \| Case index, numerical extraction recipe and reconstruction script \|

	```python
	from datasets import load_dataset
	bwb = load_dataset("IndexTeam/NAtIveLong", "bwb_metadata", split="test")
	guofeng = load_dataset("IndexTeam/NAtIveLong", "guofeng_metadata", split="test")
	assert len(bwb) == len(guofeng) == 84
	```

	The dataset viewer shows case metadata; it does not supply translation inputs.
	Do not use references, expected hashes or scoring metadata as model inputs.

	## Obtain official data

	For BWB, obtain the official Train corpus from the
	[BWB download](https://drive.google.com/drive/folders/12K1-DWmpEdqkaR_61aogdywsALDg4z1L)
	and follow its [terms](https://github.com/EleanorJiang/BlonDe/blob/main/TERMS_OF_USE).
	The released `bwb/chapter-map.jsonl` maps project-ordered chapters to physical
	upstream records, and `bwb/case-index.jsonl` provides frozen endpoints and hashes.
	This release does not include an automated BWB text reconstruction utility.
	See [BWB details](bwb/README.md) for the mapping and scoring input requirements.

	For GuoFeng, obtain V1 Train through the
	[official registration form](https://forms.gle/YqJPkfLgGmACbnbU6), then run:

	```bash
	python guofeng/reconstruct.py --source raw/train.zh --reference raw/train.en \
	--output reconstructed/guofeng
	```

	The standard-library script verifies official input hashes and all 168
	reconstructed source/reference hashes. The output directory must be new.
	See [GuoFeng details](guofeng/README.md). Reconstructed text is local material,
	subject to the upstream terms, and is not included in this public dataset.

	## Generate and evaluate

	The [evaluation guide](evaluation/README.md) documents prediction formats,
	installation, fixed scoring models and a two-document synthetic example.
	Use the frozen `zh-en-document-v3` prompt and save each final translation with
	its `case_id`. Record the inference engine, model revision, reasoning setting,
	output limit and finish reason. The 64K band describes Chinese source length;
	reserve sufficient output and total-context budget for its English translation.

	The primary score is SEGALE-COMET, using `summary.json` →
	`five_band_macro.value`: an equal-weight mean over the five length bands.
	Report BWB and GuoFeng separately, plus scored/total case coverage. Scores are
	on a 0–1 scale; chrF2 is auxiliary. Incomplete bands do not produce a valid full
	five-band score. Evaluation code includes upstream notices and licenses.

	## Limitations and provenance

	Length labels use the frozen tokenizer with 5% tolerance. Windows overlap within
	books, and these tests have been used in model development and comparison.
	GuoFeng reconstruction preserves the existing `undefined` row in two 127-dylr
	cases; it does not silently repair the frozen benchmark.

	`release_manifest.json` records the source revision and public file hashes.
	`SHA256SUMS` checks the delivered files. The original BWB text archive was
	intentionally excluded from this public release; BWB's metadata describes the
	original frozen data, not newly reselected examples.

	## Attribution and terms

	- [BWB / BlonDe](https://github.com/EleanorJiang/BlonDe): upstream source and
	[terms of use](https://github.com/EleanorJiang/BlonDe/blob/main/TERMS_OF_USE).
	- [GuoFeng](https://github.com/longyuewangdcu/GuoFeng-Webnovel): upstream source,
	non-commercial research and redistribution conditions.
	- [SEGALE](https://github.com/NVlabs/SEGALE): component notices are in
	`evaluation/NOTICE.md` and the vendored directories.
	- Model family: [Index-Translate](https://github.com/bilibili/Index-Translate).

	We grant no additional rights in underlying books or translations. The evaluation
	code is Apache-2.0 under `evaluation/LICENSE`; upstream corpus terms apply
	separately. See [LICENSE.md](LICENSE.md).

	## Citation

	If you use this benchmark, please cite the [Index-Translate technical report](https://arxiv.org/abs/2609.40181):

	```bibtex
	@techreport{indextranslate2026,
	author={Tianjiao Li and Mengran Yu and Chenyu Shi and Lusheng Zhang and
	Qisi Chen and Yanshan Zhou and Ji Qi and Jingying Liu and
	Yuang Feng and Ziang Cui and Tianxing Yan},
	title={Index-Translate: A Multilingual Translation Model Family --- Text, Speech, Controlled Dubbing, and Long-Document Translation},
	institution={Index LLM Team},
	year={2026},
	month={September},
	eprint={2609.40181},
	archivePrefix={arXiv},
	primaryClass={cs.CL},
	url={https://arxiv.org/abs/2609.40181}
	}
	```

	## Benchmark collection

	Part of the [Index-Translate Benchmarks collection](https://huggingface.co/collections/IndexTeam/index-translate-benchmarks-6ac16fee5057f40abd7d31b7).