Triple
T24947693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Straiton |
E624236
|
entity |
| Predicate | hasNearbySupermarket |
P107962
|
FINISHED |
| Object | Asda Straiton Supercentre |
—
|
NE NERFINISHED |
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: Asda Straiton Supercentre | Statement: [Straiton, hasNearbySupermarket, Asda Straiton Supercentre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbySupermarket Context triple: [Straiton, hasNearbySupermarket, Asda Straiton Supercentre]
-
A.
hasConvenienceStore
Indicates that one entity possesses, contains, or is associated with a convenience store.
-
B.
hasGroceryStores
chosen
Indicates that one entity possesses, contains, or is associated with one or more grocery stores.
-
C.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
D.
hasInformalMarketNearby
Indicates that an entity is located close to an informal or unregulated market area.
-
E.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
- 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_69e2ff22e4c48190a0444b5a044f14e8 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 18, 2026, 5:55 a.m.