Triple
T12463733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bronx Community District 11 |
E297865
|
entity |
| Predicate | planningAreaFor |
P55551
|
FINISHED |
| Object | land use |
—
|
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: land use | Statement: [Bronx Community District 11, planningAreaFor, land use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: planningAreaFor Context triple: [Bronx Community District 11, planningAreaFor, land use]
-
A.
plannedArea
Indicates that an area is designated or intended for a specific planned use or development.
-
B.
partOfPlanningRegion
chosen
Indicates that one entity is included within, or belongs to, a larger designated planning region.
-
C.
locationOfPlanning
Indicates the place or setting where the planning activity or process occurs.
-
D.
planningModelFor
Indicates that one entity serves as a planning model used to guide, simulate, or structure the planning activities related to another entity.
-
E.
planningName
Indicates that an entity has a specific name or label used within a planning or scheduling context.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.