Triple
T5024866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alva |
E112949
|
entity |
| Predicate | hasPrimaryIndustryHistory |
P3008
|
FINISHED |
| Object | textile manufacturing |
—
|
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: textile manufacturing | Statement: [Alva, hasPrimaryIndustryHistory, textile manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryIndustryHistory Context triple: [Alva, hasPrimaryIndustryHistory, textile manufacturing]
-
A.
hasHistoricIndustry
chosen
Indicates that an entity has been associated with a notable or historically significant industry or industrial activity in the past.
-
B.
hasPrincipalIndustry
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
C.
hasMajorEmployerHistory
Indicates that an entity has a documented history of employment with a major or significant employer.
-
D.
hadStateOwnershipOfIndustry
Indicates that a governing authority or state entity possessed ownership and control over a particular industry.
-
E.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd736a0f8c819091d06275954329e9 |
completed | March 20, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69bd71509e9c8190a60c1d8d04936a12 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:36 p.m.