Triple
T4145747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Programme for the Endorsement of Forest Certification (PEFC) certifications on eligible products |
E89376
|
entity |
| Predicate | complements |
P162
|
FINISHED |
| Object | other forest certification labels such as FSC on the market |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: other forest certification labels such as FSC on the market | Statement: [Programme for the Endorsement of Forest Certification (PEFC) certifications on eligible products, complements, other forest certification labels such as FSC on the market]
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af025fef088190b42515d0a854a1ae |
completed | March 9, 2026, 5:24 p.m. |
Created at: March 9, 2026, 3:43 p.m.