Datasets:

KD-Lingee
/

lingee-bench

Prefix	Tasks	Scope
`CG`	2	Multi-file merging, batch template filling
`CPV`	3	Expense compliance, policy conflicts, requirement feasibility checks
`DA`	5	Business data analysis, attribution, and rolling forecasts
`DFP`	4	Data cleaning, customer segmentation, Text2SQL, financial intelligence screening
`DIAG`	4	Error logs, root cause, and integration failure diagnosis
`DRV`	5	Contract clauses, compliance red lines, form and multi-invoice verification
`IMG`	2	Invoice and contract image recognition and reconciliation
`KBR`	4	Multi-source retrieval over the Kingdee Cloud Community knowledge base
`RQA`	3	Q&A over annual reports and ESG reports
`SCH`	3	Calendar sync, time zone conversion, date rules

Each task's inputs live in environment/ (some tasks pack them as workspace.tar.gz), gold answers and judge evidence live in tests/gold/, and the source materials are recorded in source_dataset / source_item of task.toml.

Scoring

Each task's tests/judge.yaml combines rule-based sub-scores with an LLM judge (rubric_binary_mean). The judge reads JUDGE_BASE_URL, JUDGE_MODEL, and JUDGE_API_KEY (OpenAI-compatible API) and runs in strict mode by default: when the judge is unavailable, the result must be reported separately, and must not be counted as a business score of zero or replaced with the rule-based score.

In official runs, task containers are attached only to an internal network; only the model proxy has external access.

Integrity

dataset.toml records each task's name and Harbor task package digest.