Triple
T35767141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manton Avenue |
E1034046
|
entity |
| Predicate | hasBusinessesAlong |
P43979
|
FINISHED |
| Object | retail stores |
—
|
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: retail stores | Statement: [Manton Avenue, hasBusinessesAlong, retail stores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusinessesAlong Context triple: [Manton Avenue, hasBusinessesAlong, retail stores]
-
A.
hasBusinesses
Indicates that an entity owns, operates, or is associated with one or more businesses.
-
B.
hasBusinessIn
Indicates that one entity conducts, operates, or maintains business activities within the jurisdiction, location, or domain of another entity.
-
C.
isCommercialHubAlong
Indicates that a location functions as a commercial center situated along a specified route, corridor, or geographic feature.
-
D.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
E.
hasBusinessTypeAlong
chosen
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.
- 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_69f76e13edd081909101629aa829c4ad |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: May 3, 2026, 4:06 p.m.