|
Download README.md from Olyxee/FinIR-IntentBench: direct link, hf CLI and curl.
- Browser
- Download file 7.21 kB
-
https://huggingface.co/datasets/Olyxee/FinIR-IntentBench/resolve/main/README.md
- Command line
-
hf download hf://datasets/Olyxee/FinIR-IntentBench/README.md
-
curl -L -o README.md https://huggingface.co/datasets/Olyxee/FinIR-IntentBench/resolve/main/README.md
7.21 kB
| license: apache-2.0 | |
| language: en | |
| tags: | |
| - finance | |
| - structured-generation | |
| - finir | |
| task_categories: | |
| - text-generation | |
| pretty_name: FinIR-IntentBench | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: core | |
| path: data/core.jsonl | |
| - split: stress | |
| path: data/stress.jsonl | |
| # Dataset Card: FinIR-IntentBench v1 | |
| ## Purpose | |
| Paired `{natural-language finance instruction, expected FinIR Intent}` examples for | |
| evaluating any FinIR-Intent compiler (the rule-based baseline, a fine-tuned model, or | |
| an LLM-backed one) against the canonical **FinIR Intent Contract** (schema `1.0`, | |
| owned by the core `finir` package — `finir.intent.json_schema()` / | |
| `schemas/finir-intent-v1.schema.json`, runtime `>=0.1.0,<0.2.0`). | |
| ## Size and splits | |
| - **183 examples total.** | |
| - **`core` (143)** — in-distribution phrasing the deterministic baseline is built to | |
| support. | |
| - **`stress` (40)** — a held-out subset of harder paraphrases (unlisted verbs, | |
| fractions, magnitude suffixes, idioms, out-of-domain phrasing) authored | |
| **independently of the baseline's rules**. The baseline was deliberately not tuned | |
| to these; they exist so evaluation reports a real coverage gap rather than a score | |
| the parser was fitted to. See the split methodology below and `../MODEL_CARD.md`. | |
| The `difficulty` field on every row records the split. | |
| ## Categories | |
| | category | total | core | stress | covers | | |
| |---|---|---|---|---| | |
| | `valid_simple` | 118 | 90 | 28 | one operation (`relative_change` / `set` / `absolute_change`) across every supported target | | |
| | `ambiguous` | 21 | 16 | 5 | vague quantities, no target, conflicting duplicate targets, "set to N%" on a non-percentage target | | |
| | `unsupported` | 17 | 13 | 4 | clear but not a FinIR model mutation (acquisitions, IPOs/going public, layoffs, litigation, hiring, bankruptcy, spin-offs) | | |
| | `multi_operation` | 10 | 9 | 1 | multiple simultaneous operations in one instruction | | |
| | `invalid` | 7 | 5 | 2 | structurally valid, semantically wrong at execution (currency or unit mismatch) | | |
| | `range` | 6 | 6 | 0 | a `range` batch sweep | | |
| | `scenario` | 4 | 4 | 0 | named `scenarios`, each with simultaneous operations | | |
| Every one of the 12 supported targets (`revenue`, `cogs`, `opex`, `payment_terms`, | |
| `accounts_payable`, `inventory`, `capex`, `debt`, `interest_rate`, `cash`, `price`, | |
| `volume`) and every operation type (`set`, `relative_change`, `absolute_change`, | |
| `range`, multi-operation, `scenarios`), unit (`money`, `percentage`, `days`, | |
| `quantity`) and currency (`ZAR`, `USD`) appears in the dataset. | |
| ## Format | |
| One JSON object per line in `examples/intentbench_v1.jsonl`: | |
| ```json | |
| {"id": "...", "category": "...", "difficulty": "core|stress", "text": "...", | |
| "expected_intent": { ...canonical FinIR Intent envelope... }} | |
| ``` | |
| 9 examples (`id` prefixed `canon_`) instead carry a `fixture` field naming a file in | |
| the core repo's `tests/fixtures/intents/` — the exact fixtures | |
| `tests/test_intent_contract.py` validates and executes on the runtime side. The repo | |
| copy references them by filename (rather than re-typing their JSON) so the benchmark | |
| and the runtime can never drift apart on those cases; the **Hugging Face export** | |
| (`../release/huggingface/finir-intentbench/`) resolves them inline so the dataset | |
| loads with no dependency on the GitHub repo (see "Loading" below). | |
| Seven rows whose `expected_intent` is structurally `"valid"` but semantically wrong | |
| for the reference model carry `"execution_expectation": "semantic_reject"` — the | |
| evaluation checks the runtime correctly raises `finir.intent.IntentValidationError`, | |
| proving the NL layer transcribes faithfully and lets the runtime catch the error. | |
| ## Loading (Hugging Face Datasets) | |
| The Hugging Face export ships fully inlined JSONL (no `fixture` references; the | |
| `expected_intent` is a JSON string to keep a stable, flat schema), plus per-split | |
| files: | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("Olyxee/FinIR-IntentBench") # 'core' and 'stress' splits | |
| core = load_dataset("Olyxee/FinIR-IntentBench", split="core") | |
| import json | |
| row = core[0] | |
| expected = json.loads(row["expected_intent"]) # the canonical envelope | |
| ``` | |
| No clone of the FinIR GitHub repo is required to use the dataset. | |
| ## Generation methodology | |
| - **Fully synthetic.** No real company data, no data from any real financial system. | |
| All values are illustrative and generic. | |
| - Ground-truth expected intents are derived from a structured spec (target, | |
| operation, direction, magnitude) — **not** by running the baseline parser — so the | |
| benchmark measures the parser rather than being defined by it (`../` generator in | |
| the workstream; see `../MODEL_CARD.md`). | |
| - The 9 `canon_*` rows reuse the core repo's shared fixtures verbatim. | |
| - **Human-reviewed:** every row was reviewed for a correct canonical envelope and | |
| correct split label; the core subset is additionally gated by a test asserting the | |
| baseline reaches 100% status accuracy on it, and every expected intent is checked | |
| against the canonical JSON Schema in CI. | |
| ## Split methodology (anti-leakage) | |
| `core` is phrasing inside the documented rule set; `stress` is held-out paraphrases | |
| authored to fall outside it. A benchmark hand-tuned until the parser passes every | |
| case measures nothing — so the baseline is frozen against the stress subset. On the | |
| current baseline the stress subset scores well below core (status 0.70 vs 1.00, value | |
| 0.58 vs 1.00), which is the intended, honest signal. When a stress case is genuinely | |
| fixed in the rule set, it may move to `core` with regression coverage; new | |
| adversarial paraphrases are added to `stress` to keep the gap measurable. | |
| ## What is not in this dataset | |
| - No `period`/time-scope field (forbidden by the v1.0 contract). | |
| - No private company, customer, or personal data — entirely synthetic. | |
| - No canonical alias ontology: targets are the raw FinIR model-input names; synonym → | |
| target mapping is the compiler's job, not the dataset's or the contract's. | |
| ## Versioning | |
| Filename-versioned (`intentbench_v1.jsonl`). A breaking change to the FinIR Intent | |
| Contract (a `schema_version` major bump) requires a new IntentBench major version, per | |
| `docs/intent-contract.md#versioning-policy`. Additive cases can be appended without a | |
| version bump. | |
| ## License & attribution | |
| Apache-2.0, matching the core FinIR repository. FinIR-IntentBench was contributed by | |
| **Alisha Fatima** ([@AlishaFatima16](https://github.com/AlishaFatima16)) as part of | |
| the FinIR-Intent Hugging Face workstream; the canonical contract it targets is | |
| maintained by Olyxee. | |
| ## Files | |
| - `data/intentbench_v1.jsonl` — all 183 examples (each `expected_intent` is a JSON string). | |
| - `data/core.jsonl` — 143 core examples. | |
| - `data/stress.jsonl` — 40 held-out stress examples. | |
| ## Links | |
| - **FinIR-Intent (model/baseline):** https://huggingface.co/Olyxee/FinIR-Intent | |
| - **FinIR source (GitHub):** https://github.com/Olyxee/finir | |
| - **Intent Contract spec:** https://github.com/Olyxee/finir/blob/main/docs/intent-contract.md | |