Triple
T2009631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stella McCartney |
E43661
|
entity |
| Predicate | usesMaterialsPolicy |
P34453
|
FINISHED |
| Object | does not use leather |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
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: does not use leather | Statement: [Stella McCartney, usesMaterialsPolicy, does not use leather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMaterialsPolicy Context triple: [Stella McCartney, usesMaterialsPolicy, does not use leather]
-
A.
usesPolicyModel
Indicates that one entity applies, relies on, or operates according to a particular policy model.
-
B.
issuesPolicyOn
Indicates that an authority or organization formally creates, approves, or enacts a policy concerning a particular subject or domain.
-
C.
supportsPolicy
Indicates that one entity endorses, backs, or is in favor of a particular policy or set of policies.
-
D.
usesPrinciple
Indicates that one entity applies, relies on, or is based upon a particular principle in its functioning, reasoning, or design.
-
E.
implementedPolicy
Indicates that a particular policy has been put into effect or carried out by an entity.
- F. None of above. chosen
Provenance (4 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb89be08c81909eb5ea672ea46b2b |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb83e7888819096dc40275c77daff |
completed | March 7, 2026, 5:31 a.m. |
Created at: March 4, 2026, 7:37 p.m.