PatentAgentBench
Collection
PatentAgentBench (PAB) is a benchmark comprising 8 professional patent-related tasks for evaluating LLM agents. • 8 items • Updated • 1
Datasets:
field_values dict | scoring_policy dict | layer_weights dict | metrics listlengths 19 19 |
|---|---|---|---|
{
"id": 13,
"apno": "EP2013875593",
"country": "EP",
"applicants": "Halliburton Energy Services, Inc.",
"notify_type": null,
"q_mrdt": "20160629",
"notify_content": "<!-- Page 1 -->\n\n| Datum<br>Date<br>Date | cf Form 1507 | Blatt<br>Sheet<br>Feuille | 1 | Anmelde-Nr:<br>Application No:<br>Demande n°: | ... | {
"rule_version": "oar_bench_common_19_2026-10-20",
"metric_count": 19,
"score_values": [
0,
0.5,
1
],
"subjective_metrics": "The Judge returns 0, 0.5, or 1 for each scored criterion using its own levels. G3-G5 additionally follow the synchronized zero-score rule below. The Judge does not calculat... | {
"common": 1
} | [
{
"metric_id": "G1",
"name": "Accuracy of understanding the case facts and Office Action",
"evaluation_object": "Whether the application, its current claims, the Office Action, and the relevant cited documents are correctly understood, and whether the validity of the grounds for objection is correctly a... |
{"id":27,"apno":"EP2018937981","country":"EP","applicants":"UPM-Kymmene Corporation","notify_type":n(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
{"id":54,"apno":"EP2011075105","country":"EP","applicants":"New England Biolabs, Inc.","notify_type"(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
{"id":60,"apno":"EP2011741502","country":"EP","applicants":"Dow Global Technologies LLC","notify_typ(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
{"id":82,"apno":"EP2017184017","country":"EP","applicants":"Fujitsu Limited","notify_type":null,"q_m(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
{"id":92,"apno":"EP2017201795","country":"EP","applicants":"Sumitomo Rubber Industries, Ltd.","notif(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
{"id":93,"apno":"EP2013770071","country":"EP","applicants":"Kyushu University, National University C(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
{"id":106,"apno":"US15601685","country":"US","applicants":"CASTRO ET AL.","notify_type":"Non-Final R(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
{"id":120,"apno":"US10569113","country":"US","applicants":"TAKAMATSU ET AL.","notify_type":"Non-Fina(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
{"id":136,"apno":"US13221391","country":"US","applicants":"MOLLINGER ET AL.","notify_type":"Non-Fina(...TRUNCATED) | {"rule_version":"oar_bench_common_19_2026-10-20","metric_count":19,"score_values":[0.0,0.5,1.0],"sub(...TRUNCATED) | {
"common": 1
} | [{"metric_id":"G1","name":"Accuracy of understanding the case facts and Office Action","evaluation_o(...TRUNCATED) |
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PatSnap Patent OAR Bench
A benchmark dataset for patent Office Action Response (OAR) tasks. The test split contains 40 cases: 13 CN, 13 EP, and 14 US. It includes 40 Office Action PDF documents totaling 229 pages, structured case materials, and 19 shared Judge-scored criteria per case (760 entries).
- Dataset:
data/test.parquet, 40 cases in Parquet format. - Office Action PDFs:
assets/, namedOAR-<id>.pdfusingfield_values.idfrom each record. - Detailed source documentation (JSONL layout): English · 中文.
- Source: PatSnap/PatentAgentBench/OAR-bench.
from datasets import load_dataset
from huggingface_hub import hf_hub_download
test = load_dataset("PatSnap/patent-oar-bench", split="test")
case = test[0]
pdf = hf_hub_download(
"PatSnap/patent-oar-bench",
f"assets/OAR-{case['field_values']['id']}.pdf",
repo_type="dataset",
)
The records contain both task material and evaluator reference information. An evaluation setup should define which fields are exposed as model input. The detailed documentation describes the supplied JSONL source package and its asset/ directory. On Hugging Face, data/test.parquet is the published test split and assets/ contains the same 40 PDF files. This release contains no expert annotations, case-specific criteria, or automatic scoring metrics.
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