Triple
T38497093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYPD 103rd Precinct |
E919723
|
entity |
| Predicate | neighborhoodCoverage |
P19200
|
FINISHED |
| Object | southeastern Queens |
—
|
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: southeastern Queens | Statement: [NYPD 103rd Precinct, neighborhoodCoverage, southeastern Queens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neighborhoodCoverage Context triple: [NYPD 103rd Precinct, neighborhoodCoverage, southeastern Queens]
-
A.
neighborhoodRadius
Indicates the maximum distance around a reference entity within which other entities are considered to be in its neighborhood.
-
B.
regionCoverage
chosen
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
C.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
D.
occurredInNeighborhood
Indicates that an event or action took place within the boundaries of a specific neighborhood.
-
E.
accessesNeighborhood
Indicates that one entity has the ability or permission to enter, reach, or make use of a particular neighborhood.
- 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_69f76e9ddd4481908f8c04439d848f9d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:31 p.m.