Triple
T9953702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moe’s Tavern |
E195392
|
entity |
| Predicate | hasAlternateBusinessUse |
P78228
|
FINISHED |
| Object | family restaurant (temporary) |
—
|
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: family restaurant (temporary) | Statement: [Moe’s Tavern, hasAlternateBusinessUse, family restaurant (temporary)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateBusinessUse Context triple: [Moe’s Tavern, hasAlternateBusinessUse, family restaurant (temporary)]
-
A.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
B.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
-
C.
hasCommercialFunction
Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
-
D.
hasSubsidiaryBusiness
Indicates that one business entity owns or controls another business entity as its subsidiary.
-
E.
hasSecondaryUsage
chosen
Indicates that an entity is associated with an additional, non-primary function or purpose beyond its main intended use.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb694b95481909d049302818e7137 |
completed | April 2, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:46 p.m.