Triple
T24715648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarehall |
E612150
|
entity |
| Predicate | hasNearbyRetail |
P5648
|
FINISHED |
| Object | Northern Cross retail area |
—
|
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: Northern Cross retail area | Statement: [Clarehall, hasNearbyRetail, Northern Cross retail area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyRetail Context triple: [Clarehall, hasNearbyRetail, Northern Cross retail area]
-
A.
hasConvenienceStore
Indicates that one entity possesses, contains, or is associated with a convenience store.
-
B.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
C.
hasNearbyFacility
chosen
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
D.
hasMajorCompanyNearby
Indicates that a location or entity is situated close to at least one large or significant company.
-
E.
hasRetailArea
Indicates that an entity possesses or includes a designated space used for retail or commercial sales activities.
- 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_69e2d7d6e7a48190bb43b0d8bb1137a0 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 3:36 a.m.