| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - evaluation |
| - workflows |
| configs: |
| - config_name: cases |
| default: true |
| data_files: |
| - split: test |
| path: data/cases.parquet |
| - config_name: questions |
| data_files: |
| - split: test |
| path: data/questions.parquet |
| - config_name: run_results |
| data_files: |
| - split: test |
| path: data/run_results.parquet |
| --- |
| |
| # Invoice processing |
|
|
| Snapshot: 2026-09-28. 150 cases and 6,874 question instances. |
| Default reference: **consensus**. Labels are model-generated references. |
|
|
| ## Data |
|
|
| Load configuration `cases`, `questions`, or `run_results`; all have a `test` split. |
|
|
| - **cases:** one row per `case_id`, with the complete input in `input_json`, descriptive |
| `metadata_json`, and `openai`, `anthropic`, and `consensus` labelsets. Decisions are grouped |
| by `policy_id` and contain `status`, `actions`, and `primary_action`. |
| - **questions:** one row per distinct case/node/question/input combination, identified by |
| `question_instance_id`. `question_json` and `state_json` describe |
| the model input. Each labelset contains `answer_json`, `probabilities`, `confidence`, |
| `confidence_method`, and `expected_score` for score questions. `answer_json` is the modal |
| answer (null for ties); the expected score is a separate numeric value. |
|
|
| Independent labels include the actual model, reasoning effort, question mode, and |
| `used_opus_fallback`. Missing labels have explicit status and null values; the case is retained. |
| Question status `not_answered` means that reference did not answer that question instance. |
|
|
| ## Scoring |
|
|
| `dataset.json` lists policy IDs and the applicable comparison rules: |
|
|
| - `exact_actions`: compare complete action sets including arguments; ignore order and duplicates. |
| - `primary_action`: compare the designated primary action including its arguments. |
|
|
|
|
| ## Run results |
|
|
| `run_results` contains 9 code-route runs selected by the final plots: |
| 1,350 rows, one per `run_id` and `case_id`, with 61,866 |
| recorded question answers. The `test` split contains every exported row; nothing is partitioned. |
|
|
| Each row includes the model's name, provider, reasoning effort, and question mode; |
| execution `status`, `cost_usd`, `wall_time_s`, `summed_call_time_s`, token counts, and call count; |
| and two nested lists: |
|
|
| - `questions`: `node_id`, `question_id`, `kind`, the actual `question_json` and `state_json`, |
| `status`, `answer_json`, `probabilities`, `expected_score`, `confidence`, and `confidence_method`. |
| Inputs are repeated so each result is self-contained. Answers are the recorded run values; |
| `expected_score` is calculated from the distribution for score questions. Only recorded |
| questions appear: branches not taken do not produce fabricated answers. Dynamic choice |
| options are preserved exactly, including instances absent from the reference question table. |
| - `decisions`: `policy_id`, `status`, `actions`, `primary_action`, and `scores`. Each score has |
| `metric_id` and a boolean `value` against the **consensus** reference (null when inapplicable). |
| Metrics use only `exact_actions` or `primary_action` comparisons. |
|
|
| Runs use exactly the consensus scoring cases in `cases`. Prediction errors remain in scoring |
| and count as wrong. Measurements are per case, shared across policy decisions; missing |
| measurements remain null. Cost is recorded in USD using the basis named in each run summary. |
|
|
| `dataset.json` contains `runs`, keyed by `run_id`, with plotted aggregate scores, denominators, |
| mean cost/time, and measurement counts. The selected run for a model configuration is the one |
| used by the plot (highest primary accuracy), not necessarily its newest execution. Overall |
| plot points average workflows equally for configurations present in all four workflows. |
|
|
| ## Consensus |
|
|
| Question-level consensus averages the available probability distributions for the same question |
| and input. `contributors` and `weights` specify 0.5 each for two sources or 1.0 for a single |
| source. Consensus confidence is the maximum blended probability. |
|
|
| Case-level consensus contains the final reference actions from applying the workflow to its |
| blended signals. These are the references used for evaluation. Distinct dynamic question |
| instances remain separate in the question table. |
|
|
| ## Coverage |
|
|
| | Labelset | Cases with decisions | Opus fallback cases | |
| |---|---:|---:| |
| | openai | 150 | 0 | |
| | anthropic | 150 | 0 | |
| | consensus | 150 | 0 | |
|
|
| ## Encoding |
|
|
| Fields ending in `_json` are JSON-encoded text; decode with `json.loads`. |
| Probability distributions are lists of `option`/`probability` pairs. Action arguments are |
| preserved in `arguments_json`. Descriptive metadata is separate from model-visible state. |
|
|
| ## License |
|
|
| This dataset is licensed under the [Apache License 2.0](LICENSE). |
|
|
