Triple
T445741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Township, Mercer County, New Jersey |
E7014
|
entity |
| Predicate | hasShoppingCenters |
P4285
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Lawrence Township, Mercer County, New Jersey, hasShoppingCenters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoppingCenters Context triple: [Lawrence Township, Mercer County, New Jersey, hasShoppingCenters, true]
-
A.
hasShoppingDistrict
chosen
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
-
B.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
C.
hasRentalCarCenter
Indicates that a location or facility includes or is associated with a rental car center where vehicles can be rented.
-
D.
isCommercialHubIn
Indicates that a place functions as a primary center of commercial or business activity within a specified larger area or region.
-
E.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef479ec08190a659eead6eb0d4d0 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2eddfb5508190a4e06e1b260d8b2b |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.