Triple
T32706391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota Antelopes |
E836282
|
entity |
| Predicate | hasOwnerIndustry |
P13077
|
FINISHED |
| Object | automotive |
—
|
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: automotive | Statement: [Toyota Antelopes, hasOwnerIndustry, automotive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOwnerIndustry Context triple: [Toyota Antelopes, hasOwnerIndustry, automotive]
-
A.
hasPrincipalIndustry
chosen
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
B.
hasCustomerIndustry
Indicates that a customer is associated with or operates within a particular industry or sector.
-
C.
hadStateOwnershipOfIndustry
Indicates that a governing authority or state entity possessed ownership and control over a particular industry.
-
D.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
E.
hasIPOwner
Indicates that one entity holds ownership or legal rights over the intellectual property associated with another entity.
- 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_69f3493446148190819541f3ffe79975 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c851d2488190a93924bca6b167d1 |
completed | May 3, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:10 a.m.