Triple
T13081980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn Law School |
E310229
|
entity |
| Predicate | cityGovernmentProximity |
P12057
|
FINISHED |
| Object | near Brooklyn Borough Hall |
—
|
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: near Brooklyn Borough Hall | Statement: [Brooklyn Law School, cityGovernmentProximity, near Brooklyn Borough Hall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityGovernmentProximity Context triple: [Brooklyn Law School, cityGovernmentProximity, near Brooklyn Borough Hall]
-
A.
governingBodyNearby
chosen
Indicates that a governing body is located in close physical proximity to the referenced entity or area.
-
B.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
C.
administrativeCentreNearby
Indicates that an administrative centre is located close to the referenced entity in geographic or spatial terms.
-
D.
nearbyPoliticalEntity
Indicates that one political entity is geographically close to another political entity, without necessarily sharing a border.
-
E.
campusProximity
Indicates that one entity is located near, adjacent to, or within a short distance of a campus associated with the other entity.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d9811add9881908a92186dab5b6d48 |
completed | April 10, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69d9803f6c508190bfadfbc2d00c2c64 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:01 p.m.