Triple
T25049751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musée du Peigne et de la Plasturgie |
E627342
|
entity |
| Predicate | materialCovered |
P117898
|
FINISHED |
| Object | natural materials used for combs |
—
|
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: natural materials used for combs | Statement: [Musée du Peigne et de la Plasturgie, materialCovered, natural materials used for combs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialCovered Context triple: [Musée du Peigne et de la Plasturgie, materialCovered, natural materials used for combs]
-
A.
coversMaterialType
chosen
Indicates that one entity includes, addresses, or applies to a specified type of material.
-
B.
brandCovered
Indicates that one entity provides coverage, representation, or inclusion for a particular brand within its scope (e.g., in a policy, service, catalog, or offering).
-
C.
eraCovered
Indicates that one entity temporally encompasses, includes, or spans the historical period or era associated with another entity.
-
D.
surfaceCover
Indicates that one entity forms the material or layer that covers the outer surface of another entity.
-
E.
coverText
Indicates that one text serves as the cover or front-facing textual representation for another work or resource.
- F. None of above.
Provenance (3 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_69e2ff2b4c80819087c916b2b16241b9 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:08 a.m.