Watershed-Climate/PCFBench
PCFBench Paper: arXiv:2608.27716 · Code: watershed-climate/pcfbench Process-based Product Carbon Footprint benchmark for evaluating LLMs and agents on the operational steps of life-cycle assessment (LCA): bill-of- materials decomposition, mapping triage, ecoinvent process matching, literature extraction of physical input rates, and total kgCO₂e prediction against expert-grounded EPDs. Tasks ID Task Items GT claims Headline metric 1 Product decomposition… See the full description on the dataset page: https://huggingface.co/datasets/Watershed-Climate/PCFBench.
PCFBench
Paper: arXiv:2608.27716 · Code: watershed-climate/pcfbench
Process-based Product Carbon Footprint benchmark for evaluating LLMs and agents on the operational steps of life-cycle assessment (LCA): bill-of- materials decomposition, mapping triage, ecoinvent process matching, literature extraction of physical input rates, and total kgCO₂e prediction against expert-grounded EPDs.
Tasks
(Step 6 is deterministic arithmetic and not separately evaluated.)
Files
Schema
Every task row uses the same envelope:
{
"id": "...",
"input": { /* task-specific */ },
"expected_output": { /* task-specific ground truth */ },
"metadata": {
"product_category": "Metal, mineral, plastic & glass products",
/* task-specific extras: vagueness_severity, request_id, tags=[n_components_*], ... */
}
}The 12 environdec-aligned product categories used across tasks are: Chemical products, Construction products, Electricity / steam / fuels, Food & beverages, Furniture & other goods, Infrastructure & buildings, Machinery & equipment, Metal, mineral, plastic & glass products, Paper and plastic products, Services, Textiles, footwear & apparel, Vehicles & transport equipment. All tasks except Tasks 4–5 currently miss Infrastructure & buildings; Tasks 4–5 cover a subset because the extraction documents are concentrated in industrial-process literature.
See DATASHEET.md for the full Datasheet for Datasets, including collection process, annotation protocol, intended uses, and limitations.
Loading
Each task is a separate config:
from datasets import load_dataset
decomposition = load_dataset("Watershed-Climate/PCFBench", "task1_decomposition", split="train")
epd = load_dataset("Watershed-Climate/PCFBench", "task7_epd", split="train")The files are plain JSONL, so pandas.read_json(..., lines=True) or json.loads per line work equally well on a local copy.
The companion code repository at watershed-climate/pcfbench provides a ready-to-run eval harness for all 6 task variants.
Citation
@misc{pcfbench2026,
title = {PCFBench: A Diagnostic Benchmark for Product Carbon Footprint Estimation},
author = {Rao, Krishna and Dumit, Andrew and Ulissi, Shaena and
Feintzeig, Jacob and Joyce, P. James and Frank, Daniel and
Watson, Steven and Glidden, Jonathan and Dinc, Gizem Ilayda and
Kwee, Travis M.},
year = {2026},
eprint = {2608.27716},
archivePrefix = {arXiv}
}License
CC BY-NC-SA 4.0.
task7_epd.jsonl references publicly disclosed Environmental Product Declarations from environdec.com; each item retains the original EPD's source_url.
