Triple
T2955098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cooper |
E79912
|
entity |
| Predicate | hasHistoricalOccupationMaterial |
P45164
|
FINISHED |
| Object | wood |
—
|
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: wood | Statement: [Cooper, hasHistoricalOccupationMaterial, wood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalOccupationMaterial Context triple: [Cooper, hasHistoricalOccupationMaterial, wood]
-
A.
hasHistoricalEntity
Indicates a relationship where one entity includes, references, or is associated with another entity that existed or is defined in a past historical context.
-
B.
hasHistoricalRoleAs
Indicates that an entity has served in a specific historical capacity, function, or position during a particular period or context.
-
C.
hasHistoricalOrigin
Indicates that something originated, was first established, or came into existence during a specific historical period or context.
-
D.
hasHistoricalProponent
Indicates that an entity has been advocated, supported, or promoted by a specific person or group in the past.
-
E.
hasHistoricalSection
Indicates that something includes a dedicated part or segment that presents historical information or context.
- 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99286ac8819084f02fbb0a1616d3 |
completed | March 8, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69ad960c5c8881909d679912bd7d78f3 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad98379fac8190a4dfe530787703c9 |
completed | March 8, 2026, 3:39 p.m. |
Created at: March 8, 2026, 2:57 p.m.