[Fix] ELBench: scope the safety metric correctly and fix data-loading docs

[YL1N]

Motivation

Two problems in the ELBench port added in #2495. I am on the ELBench team, so
this corrects our own contribution. No data, prompt, or scoring logic is changed
— this is naming and documentation only.

1. The Safety metric is scoped to one non-discriminative family

ELBench's safety module has five task families. The public dataset ships
only the benign-answering one (安全可信/通用-应回答/安全回答.jsonl, 250
items). The other four — harmful-request refusal, safe guidance, teaching
safety, adversarial robustness — are deliberately withheld because their
prompts contain harmful / jailbreak content. This is stated on the
dataset card.

The port labels that single family 安全可信 Safety with no qualification and
exposes it as elbench_safety_应回答. That reads as an overall safety score,
but the family only asks whether a model answers benign questions without
over-refusing. In the ELBench authors' evaluation every model scores 98.4–100
on it, so it does not separate models — and a model with no safety guardrails
at all would also score near 100, because nothing in the shipped subset tests
refusal.

Changes:

• abbr: elbench_safety_应回答 → elbench_safety_benign_answering
• ELBENCH_SAFETY_TASKS value: 应回答 → benign_answering
• README table row + footnote: the five families, which four are withheld and
  why, and a note not to report this number as "ELBench safety"
• The same note in the module docstring

The rename also drops non-ASCII characters from an abbr that ends up in
output filenames and summarizer columns; the other ELBench abbrs are already
ASCII.

2. Three README statements contradict the loader

README says	Loader actually does
data is "downloaded automatically … on first run"	_elbench_data_root() downloads only when DATASET_SOURCE is HF or ModelScope; unset → local mode → FileNotFoundError
"set ELBENCH_DATA_ROOT to use a local copy"	ELBENCH_DATA_ROOT is never read — the only os.environ.get call is for DATASET_SOURCE. The module docstring even says "No ELBench-specific env var is needed."
"accepts either this root-level layout or a benchmark_root/ wrapper"	_elbench_path() joins root/subdir/name.ext directly; there is no wrapper fallback

Following the README's "How to run" verbatim fails on a clean checkout. Fixed
by documenting the actual DATASET_SOURCE behaviour in a table and adding
DATASET_SOURCE=HF to the run examples.

Two smaller doc corrections in the same files: the high-level-edu judge reports
10 * mean(1..10), i.e. 10–100 rather than the documented 0–100; and the
docstring pointed at a stale benchmark_root/基本教育 path.

Breaking change

elbench_safety_应回答 → elbench_safety_benign_answering changes a result
key. ELBench landed about a month ago and this rename is the point of the fix,
so I judged the churn acceptable — happy to add a backwards-compatible alias
instead if you would prefer.

Verification

• Both modified .py files parse (ast.parse); the edits touch only comments,
  docstrings and one string literal.
• I have not run an end-to-end evaluation or OpenCompass's pre-commit hooks
  locally for this change, since the diff is naming and documentation only.
  Happy to do so if you want it before merge.

[YL1N]

Pushed a second commit. While checking the links in this file I found two of them are dead, so the scope grew slightly — still docs only.

1. https://github.com/ZeroLoss-Lab/ELBench returns 404.

It appears in the README introduction, the README BibTeX, and the elbench.py module docstring — all added by #2495. The ZeroLoss-Lab org exists but has no public ELBench repo. All three now point at the HuggingFace dataset, which resolves:

$ curl -o /dev/null -w '%{http_code}' -L https://github.com/ZeroLoss-Lab/ELBench
404
$ curl -o /dev/null -w '%{http_code}' -L https://huggingface.co/datasets/ZeroLoss-Lab/ELBench
200

dataset-index.yml also has paper: https://github.com/ZeroLoss-Lab/ELBench. I left it alone to keep this PR scoped — happy to fix it here if you'd rather.

2. DATASET_SOURCE=ModelScope cannot work — the dataset is not on ModelScope.

datasets_info.py registers ms_id: ZeroLoss-Lab/ELBench, but that dataset does not exist. The web URL returns 200, which is a soft 404 from the SPA; the API is unambiguous:

$ curl -s https://www.modelscope.cn/api/v1/datasets/ZeroLoss-Lab/ELBench
{"Code":10020101002,"Message":"不存在的数据集",...}

So my first commit documented a ModelScope option that always fails. The table now marks it unavailable and says HuggingFace is the only working source, with the same note in the loader comment. I did not touch the ms_id entry in datasets_info.py — leaving it means the path starts working as soon as the dataset is mirrored, and removing it would be a behaviour change rather than a doc fix. Let me know if you'd prefer it dropped.