Triple
T10970088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYPD 102nd Precinct |
E259210
|
entity |
| Predicate | jurisdiction |
P82
|
FINISHED |
| Object | Woodhaven |
E164414
|
NE 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: Woodhaven | Statement: [NYPD 102nd Precinct, jurisdiction, Woodhaven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woodhaven Context triple: [NYPD 102nd Precinct, jurisdiction, Woodhaven]
-
A.
Woodhaven
chosen
Woodhaven is a residential neighborhood in the borough of Queens, New York City, known for its diverse community and proximity to major transit lines and Forest Park.
-
B.
Edgewater
Edgewater is a waterfront neighborhood in Miami known for its high-rise residential buildings and proximity to both Biscayne Bay and the city’s urban core.
-
C.
Edgewater
Edgewater is a small coastal city in east-central Florida known for its location along the Indian River in Volusia County.
-
D.
Edgewater
Edgewater is a lakefront community area on Chicago’s North Side known for its dense urban neighborhoods, historic architecture, and proximity to Lake Michigan.
-
E.
Welhaven
Welhaven is a Norwegian surname most notably associated with the 19th-century poet and critic Johan Sebastian Welhaven.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77198e5408190904b2bb603d1bc16 |
completed | April 9, 2026, 9:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344a2130081908d9d22ee84890925 |
completed | April 18, 2026, 8:45 a.m. |
Created at: April 8, 2026, 9:24 p.m.