| --- |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| |
| # finance-data — DHR / ILMN M&A Analysis Tasks |
|
|
| Investment-banking analysis tasks set in a (fictional) strategic M&A project |
| where Danaher (DHR) explores acquiring Illumina (ILMN). Each task gives an |
| agent a prompt plus a full deal-room of reference materials (financial models, |
| spreadsheets, PDFs, research) and grades the answer against a per-criterion |
| rubric. Tasks that require modifying a workbook also ship the expert's gold |
| workbook as a deliverable file. |
|
|
| ## Layout |
|
|
| ``` |
| data/ # the task table (parquet, 3 rows) |
| reference_folder/ # the shared deal-room every task works from |
| ├── filesystem/ # models, filings, research, deal docs (xlsx/pdf/pptx/…) |
| └── .apps_data/ # app state (mail, calendar, chat) for the simulated environment |
| deliverable_files/ # gold deliverable workbooks, one subfolder per task |
| ``` |
|
|
| All tasks share **one reference folder** — they are set in the same deal. The |
| `reference_folder` column holds its repo-relative path. |
|
|
| ## Columns |
|
|
| | Column | Type | Description | |
| |---|---|---| |
| | `task_id` | string | e.g. `task_helix_dhr_ilmn_06` | |
| | `sector` | string | `Finance and Insurance` | |
| | `occupation` | string | `Investment Banking Analyst` | |
| | `prompt` | string | Self-contained task instructions (includes scenario framing) | |
| | `reference_folder` | string | Repo-relative path to the shared deal-room (`reference_folder`) | |
| | `deliverable_files` | list[string] | Repo-relative paths to the gold deliverable workbook(s); empty for answer-only tasks | |
| | `gold_response` | string | The expert gold answer (text) | |
| | `rubric_pretty` | string | Human-readable rubric | |
| | `rubric_json` | string | JSON-encoded rubric (see below) | |
|
|
| ## Rubric format (`rubric_json`) |
| |
| A JSON array; each entry is one grading criterion with fields: |
| |
| - `verifier_id`, `index` — identity/ordering |
| - `criteria` — the criterion text |
| - `criteria_explanation` — step-by-step reference reasoning for the grader |
| - `weight` — contribution to the weighted task score |
| - `is_primary_objective` — a task passes only if **all** primary criteria pass |
| - `tolerance.type` / `tolerance.low` / `tolerance.high` / `tolerance.units` — |
| numeric acceptance band (e.g. exact, absolute_range) |
| - `dependencies` — criteria that must pass for this one to be meaningful |
| - `criterion_type`, `evaluation_scope`, `expected_file_type`, `human_rating`, `tags`, `universal` |
|
|
| ## Intended harness |
|
|
| Populate a sandboxed environment from `reference_folder`, run the agent with |
| file/spreadsheet/PDF tools, and grade the final answer with an LLM judge that |
| applies each rubric criterion within its stated tolerance. A task passes iff |
| every primary-objective criterion passes. For tasks with `deliverable_files`, |
| the gold workbook shows the expected end-state of the modified model. |
|
|
