Triple
T32336841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hilltop Bayview |
E826196
|
entity |
| Predicate | nearbyCommercialArea |
P191961
|
FINISHED |
| Object | Hilltop Mall 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: Hilltop Mall area | Statement: [Hilltop Bayview, nearbyCommercialArea, Hilltop Mall area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCommercialArea Context triple: [Hilltop Bayview, nearbyCommercialArea, Hilltop Mall area]
-
A.
hasNearbyCommercialFacilities
chosen
Indicates that a place is located close to one or more commercial facilities, such as shops, restaurants, or other businesses.
-
B.
nearbyEconomicActivity
Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
-
C.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
nearbyUse
Indicates that one entity uses or operates another entity that is located nearby or in close physical proximity.
-
E.
nearbyVenue
Indicates that one venue is located close to another venue in physical space.
- 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_69f34913d9048190befaa634025232be |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: May 1, 2026, 12:48 a.m.