WorkflowEvals dataset snapshot

.gitattributes

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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
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README.md

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+---
+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.

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dataset.json

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+{
+  "title": "Invoice processing",
+  "workflow": "invoice_processing",
+  "snapshot_date": "2026-09-28",
+  "default_reference": "consensus",
+  "labelsets": [
+    "openai",
+    "anthropic",
+    "consensus"
+  ],
+  "policies": [
+    {
+      "policy_id": "startup",
+      "title": "startup"
+    },
+    {
+      "policy_id": "enterprise",
+      "title": "enterprise"
+    },
+    {
+      "policy_id": "high_volume_retailer",
+      "title": "high volume retailer"
+    }
+  ],
+  "metrics": [
+    {
+      "metric_id": "accuracy",
+      "title": "Exact action-set accuracy",
+      "comparison": "exact_actions"
+    },
+    {
+      "metric_id": "primary_match",
+      "title": "Primary action agreement",
+      "comparison": "primary_action"
+    }
+  ],
+  "blend": {
+    "method": "mean_probabilities",
+    "missing_source": "use_available_source",
+    "question_alignment": "same case, node, question definition and state"
+  },
+  "coverage": {
+    "cases": 150,
+    "questions": 6874,
+    "openai_cases": 150,
+    "openai_opus_fallback_cases": 0,
+    "anthropic_cases": 150,
+    "anthropic_opus_fallback_cases": 0,
+    "consensus_cases": 150,
+    "consensus_opus_fallback_cases": 0,
+    "runs": 9,
+    "run_results": 1350,
+    "run_questions": 61866
+  },
+  "encodings": {
+    "*_json": "JSON-encoded UTF-8 text",
+    "probabilities": "list of option/probability pairs"
+  },
+  "runs": {
+    "code-anthropic-claude-haiku-4-5-default-1bb8309e2727": {
+      "model": {
+        "name": "claude-haiku-4-5",
+        "provider": "anthropic",
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+    "selection": "Final plots: highest primary accuracy per selected model configuration.",
+    "overall_aggregation": "Equal workflow means for configurations represented in all four workflows."
+  }
+}