---
language:
  - en
license: cc-by-4.0
size_categories:
  - 1K<n<10K
task_categories:
  - text-classification
  - feature-extraction
tags:
  - patent
  - prior-art
  - freedom-to-operate
  - fto
  - office-action
  - uspto
  - epo
  - multi-jurisdiction
  - intellectual-property
  - legal-nlp
pretty_name: "Layer A — Office Action Triples for FTO Eval"
configs:
  - config_name: default
    data_files:
      - split: train
        path: "**/jurisdiction=*/filing_year=*/*.parquet"
  - config_name: us
    data_files:
      - split: train
        path: "US/jurisdiction=US/filing_year=*/*.parquet"
  - config_name: ep
    data_files:
      - split: train
        path: "EP/jurisdiction=EP/filing_year=*/*.parquet"
  # v1.2 — sibling partition aggregating per-(ref_id, citing_jurisdiction)
  # citation counts. See "Cross-citation index" below.
  - config_name: prior_art_index
    data_files:
      - split: train
        path: "prior_art_index/*/index.parquet"
---

# Layer A — Office Action Triples for FTO Evaluation

A public dataset of `(invention → cited prior art → outcome)` triples
extracted from the **USPTO Office Action Research Dataset (OARD)**
+ **USPTO Open Data Portal (ODP)** API (US slice) and the **EPO
Open Patent Services (OPS)** Register service (EP slice). Built as
the agent-evaluation substrate for
[Parallax](https://parallax.3mergen.com), an AI-native Freedom-to-
Operate (FTO) and defensive-publication platform for individual
inventors and small teams.

> **Curated by [Vox](https://vox.delivery)** (org: `v13s`).
> Parallax is a Vox product; the curation layer (annotations,
> severity tagging, schema, manifest) is © Vox 2026 under
> CC-BY-4.0. The underlying USPTO patent data is public domain.

## TL;DR

- **5 011 rows** (v1.1.20260513): 5 000 US Office Actions (filing years
  2011–2017) + 11 EP search reports (filing years 2014–2018)
- **14 Parquet shards**, partitioned by `jurisdiction × filing_year`
- Schema: `(case_id, invention, examination, prior_art[], outcome,
  provenance)` — see [Schema](#schema) below
- Two jurisdictions live (US, EP); JP gated on INPIT bulk
  credential issuance
- License: **CC-BY-4.0** on the curation; underlying patent
  documents remain in the public domain
- SHA-256 manifest at `MANIFEST.json` for byte-level
  reproducibility

## Quick start

```python
from datasets import load_dataset

# Default config returns both jurisdictions (5 011 rows).
ds = load_dataset("v13s/golden-fto-layer-a", split="train")
print(len(ds))                           # 5011

# Per-jurisdiction configs are also available.
ds_us = load_dataset("v13s/golden-fto-layer-a", "us", split="train")
ds_ep = load_dataset("v13s/golden-fto-layer-a", "ep", split="train")
print(len(ds_us), len(ds_ep))            # 5000, 11

row = ds[0]
print(row["case_id"])                    # e.g. "US-13004847-0"
print(row["invention"]["title"])         # "SYSTEM AND METHOD FOR ..."
print(row["examination"]["oa_type"])     # "rejection" | "search_report"
print(row["examination"]["rejection_reasons"])  # ["obviousness_103"]
for ref in row["prior_art"]:
    print(ref["ref_id"], ref["severity"])
    # US: "US9123456B2", "obviousness"
    # EP: "US6825941",   "novelty_destroying"
```

## Schema

Each row is a single Office Action event linked to its prior-art
citations. The full schema lives at
[`data-pipeline/src/layer_a/schema.py`](https://github.com/masterleopold/parallax/blob/main/data-pipeline/src/layer_a/schema.py)
in the source repo.

| Field | Type | Description |
|---|---|---|
| `case_id` | string | Stable id: `<jurisdiction>-<application_number>-<oa_seq>` |
| `schema_version` | string | Per-row schema version (`1.0` legacy / `1.2` post-2026-05-07) |
| `jurisdiction` | string | `US` or `EP`; `JP` in future versions |
| `source_dataset` | string | `uspto_oard` (US rows) or `epo_ops` (EP rows) |
| `extracted_at` | timestamp[s, UTC] | When this row was emitted |
| `invention` | struct | Application metadata — title, abstract, IPC/CPC codes, claims, applicant |
| `examination` | struct | OA event — `oa_date`, `oa_type` ∈ {rejection, allowance, search_report}, `rejection_reasons[]`, `examiner_id` |
| `prior_art` | list<struct> | Cited references — `ref_id`, `ref_type`, `source` (examiner/applicant), `rejection_basis`, `claims_blocked[]`, `severity`, `categories[]` (v1.2+), `metadata` |
| `outcome` | struct | Final disposition — `final_disposition`, `disposition_date`, `granted_claims[]`, `amendments_made`, `decision_source` (v1.1+) |
| `provenance` | struct | Audit trail — `parser_version`, `source_file`, `manifest_sha256`, `validation_status`, `validation_notes[]` |

### Severity enum (`prior_art[].severity`)

A 3-value severity enum that downstream consumers can join across
jurisdictions. Each jurisdiction has its own source signal:

| Severity | US (OARD signal) | EP (WIPO ST.14 search-report category) |
|---|---|---|
| `novelty_destroying` | `rejection_102=1` AND `citation_in_oa=1` | `X` or `E` (incl. multi-char `XY`, `XYI`) |
| `obviousness` | `rejection_103=1` AND `citation_in_oa=1` | `Y` |
| `background` | otherwise (PTO-892, PTO-1449 IDS) | `A`, `P`, `D`, `T`, `L`, `O`, `I` |

The EP search-report category sometimes concatenates multiple
codes (e.g. `"XY"` means the citation is BOTH novelty-relevant AND
obviousness-relevant). The lowering preserves the raw string and
the extractor maps the most-severe component to `severity`.

### `prior_art[].categories` (v1.2+)

The single-string `severity` collapses multi-character ST.14 codes
to one band (e.g. `XY` → `novelty_destroying`, dropping the
inventive-step signal). To preserve the full set, v1.2 adds a
`categories: list<string>` field with each code as its own
alphabetically-sorted entry:

| Source category | `severity` | `categories` |
|---|---|---|
| `X` | `novelty_destroying` | `["X"]` |
| `Y` | `obviousness` | `["Y"]` |
| `XY` | `novelty_destroying` | `["X", "Y"]` |
| `XYI` | `novelty_destroying` | `["I", "X", "Y"]` |
| `A` | `background` | `["A"]` |

Legacy v1.0 / v1.1 rows have `categories = []` (empty).
Jurisdictions whose source data doesn't expose ST.14 codes
(US OARD uses 35 USC § sections, not ST.14) also leave the field
empty. Filter for `len(categories) > 0` to query only ST.14-
exposed rows.

### Cross-citation index (v1.2+)

A sibling partition `prior_art_index/<jurisdiction>/index.parquet`
aggregates the cases partition by `(ref_id, citing_jurisdiction)`
so consumers can ask "how often has document X been cited" without
walking the cases data row-by-row.

```python
from datasets import load_dataset

idx = load_dataset(
    "v13s/golden-fto-layer-a", "prior_art_index", split="train",
)
# Top-cited refs in EP search reports
top = sorted(
    [r for r in idx if r["citing_jurisdiction"] == "EP"],
    key=lambda r: r["citation_count"], reverse=True,
)[:10]
for r in top:
    print(r["ref_id"], r["citation_count"], r["citing_case_ids"])
```

Index schema:

| Field | Type | Description |
|---|---|---|
| `ref_id` | string | Cited document id (e.g. `US10721059`) |
| `citing_jurisdiction` | string | Where the citing examiner sits (`EP`, `US`) |
| `citation_count` | int32 | Total times this ref appears in `prior_art[]` across cases |
| `citing_case_ids` | list<string> | Sorted set of `case_id` values that cite this ref |
| `severity_distribution` | struct | Count by severity band (`novelty_destroying`, `obviousness`, `background`) |
| `first_cited_date` | date | Earliest `examination.oa_date` across citing cases |
| `last_cited_date` | date | Latest `examination.oa_date` across citing cases |

Per-jurisdiction subdirs (`prior_art_index/EP/`, `prior_art_index/US/`)
keep the index sharded by which extractor produced it. To get a
cross-jurisdiction view, union the partition or use the default
config above which includes both.

### Rejection reason codes

Canonical 3-letter codes consistent across jurisdictions:

| Code | USC § | Description |
|---|---|---|
| `anticipation_102` | 35 USC §102 | Lack of novelty (single-reference) |
| `obviousness_103` | 35 USC §103 | Obviousness (multi-reference combination) |
| `subject_matter_101` | 35 USC §101 | Patent-eligible subject matter (Alice/Mayo/Bilski) |
| `indefiniteness_112` | 35 USC §112 | Written description / definiteness |
| `double_patenting` | non-statutory | Same invention claimed twice |

Future EP/JP releases add their statute-equivalent codes
(`novelty_epc_54`, `inventive_step_epc_56`, `novelty_jp_29_1`,
etc.) without breaking the schema.

## How was this built?

### US slice (5 000 rows)

1. **OARD bulk download** (the 4M-row USPTO Office Action
   Research Dataset, frozen at the 2017 release): manually
   browser-downloaded from
   [research.uspto.gov](https://www.uspto.gov/ip-policy/economic-research/research-datasets/office-action-research-dataset-patents),
   mirrored to [v13s/oard-2017-mirror](https://huggingface.co/datasets/v13s/oard-2017-mirror)
   for repeatable fetches
2. **office_actions.csv scan** for the first 5 000 unique
   application IDs in chronological order
3. **citations.csv filter pass** to keep only those 5 000 apps'
   citation rows (~50 MB filtered from a 4 M-row, 5 GB unfiltered
   source)
4. **USPTO ODP API** enrichment per app (60 RPM rate limit; ~85
   minutes wall-clock for the full pass)
5. **Triple construction** — the OARD's pre-classified
   `rejection_*` boolean columns + the citation rows + the ODP
   metadata combine into a `LayerATriple` per OA event

### EP slice (11 rows, new in v1.0.2)

1. **EP publications list** curated from Espacenet IPC searches
   (`G06F`, `H04L`, `A61K`), filing years 2014–2018
2. **OPS published-data full-cycle** for biblio + claims
   (epodoc/docdb format, kind-suffix fallback for older
   publications)
3. **OPS Register service** (`/rest-services/register/publication/
   epodoc/{pub}/biblio`) for search-report citations — these
   carry the WIPO ST.14 category codes, mapped to `severity` via
   the table above
4. **Two-endpoint merge per publication**: full-cycle gives the
   bibliographic context; the Register service gives the
   `prior_art[]` list. Filtered to `@cited-phase == "search"` to
   keep the high-signal X/Y/A subset
5. **Triple construction** — same `LayerATriple` shape as the US
   slice; `oa_type = "search_report"`, `outcome.final_disposition
   = "pending"` (EP grants land in a separate legal-status
   endpoint, planned for v1.1)

### Common steps (both slices)

6. **Validation**: every row passes a linking validator that
   checks temporal sanity (cited prior art filed before the
   invention), severity coherence (novelty-destroying citations
   on a granted+unamended application would be an inconsistency),
   and schema round-trip
7. **Parquet emit** partitioned by jurisdiction × filing_year,
   with a SHA-256 manifest for byte-level reproducibility
8. **HuggingFace push** under [v13s/golden-fto-layer-a](https://huggingface.co/datasets/v13s/golden-fto-layer-a)

The full pipeline source lives in the public repo at
[parallax/data-pipeline](https://github.com/masterleopold/parallax/tree/main/data-pipeline).
The release runner is
[`bin/local-extract-v1.sh`](https://github.com/masterleopold/parallax/blob/main/bin/local-extract-v1.sh).

## Known limitations

- **Sample size**: 5 011 rows are a first cut. The full OARD has
  4 M+ Office Actions; ramp-up to 50 K+ US rows in v1.1+ is
  planned. The EP slice is intentionally small (11 publications)
  to validate the OPS Register integration end-to-end before
  scaling.
- **Sparse claim text**: The ODP search endpoint returns
  bibliographic metadata (title, applicant, IPC) but not full
  claim text. Some rows have `invention.claims = []` or
  placeholder markers; full claim extraction needs a separate
  ODP call (planned for v1.1).
- **JP not yet shipped**: JP slice gated on INPIT bulk
  credential approval; see
  [docs/07-partnerships/inpit-bulk-data-application.md](https://github.com/masterleopold/parallax/blob/main/docs/07-partnerships/inpit-bulk-data-application.md).
- **EP claim ranges**: The Register service embeds claim ranges
  in the citation's bibliographic text annotation (`[Y] 5,12`).
  v1.0.3+ extracts these into `prior_art[].claims_blocked`; legacy
  v1.0.2 rows leave the list empty.
- **Mixed schema_version partition**: rows from v1.0 / v1.1 cron
  cycles carry `schema_version="1.0"` and an empty `categories[]`,
  while v1.2+ rows carry `schema_version="1.2"` and populated
  `categories[]` (when the source supports ST.14). Filter on
  `schema_version` if you need a single-version partition.
- **EP outcome field is conservative**: Without joining the OPS
  legal-status endpoint, `outcome.final_disposition` defaults to
  `pending` for EP rows. v1.1 will resolve to
  `granted` / `rejected` / `withdrawn`.
- **US outcome field is conservative**: Without joining USPTO
  PEDS (Patent Examination Data System), the same defaulting
  applies on the US slice.

## Versioning

Semantic versioning per
[golden-dataset-plan.md](https://github.com/masterleopold/parallax/blob/main/docs/06-evaluation/golden-dataset-plan.md):

- **MAJOR** — schema-incompatible (field removed, type changed)
- **MINOR** — new fields, new jurisdictions, ≥10 % data growth
- **PATCH** — parser bugfix, individual case re-validation

The HuggingFace dataset repo's git history is the canonical
release ledger. To pin a specific version in your code:

```python
ds = load_dataset("v13s/golden-fto-layer-a", revision="v1.1.20260513")
```

## Citation

If you use this dataset in academic work, please cite:

```bibtex
@dataset{vox_layer_a_2026,
  author       = {Hara, Yoichiro and {Vox}},
  title        = {Layer A — Office Action Triples for
                  Freedom-to-Operate Evaluation},
  year         = 2026,
  publisher    = {Hugging Face},
  version      = {{1.1.20260513}},
  url          = {https://huggingface.co/datasets/v13s/golden-fto-layer-a},
  note         = {Curated under CC-BY-4.0; underlying patent
                  data in the public domain}
}
```

## License

- **Curation layer (this dataset)**: [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)
  — the schema, severity tagging, and triple construction are
  © Vox 2026 and may be used / redistributed with attribution.
- **Underlying patent documents**: public domain (USPTO).
- **OARD source data**: public domain (USPTO Office of the Chief
  Economist).

## Contact

- Curator: **Yoichiro Hara** (`taisei@vox.delivery`)
- Org: [Vox](https://huggingface.co/v13s) (HF: `v13s`)
- Source repo: <https://github.com/masterleopold/parallax>
- Issues: <https://github.com/masterleopold/parallax/issues>
- Product surface: <https://parallax.3mergen.com>

For takedown requests on specific patent applications, file an
issue or email the curator. Public-domain patent data is
included in good faith; the curation layer can be redacted on
request.