Triple
T7098730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troop NYC |
E165397
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | Troop NYC |
E165397
|
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: Troop NYC | Statement: [Troop NYC, abbreviation, Troop NYC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troop NYC Context triple: [Troop NYC, abbreviation, Troop NYC]
-
A.
Troop NYC
chosen
Troop NYC is the New York State Police division responsible for state-level law enforcement operations within New York City.
-
B.
Times Square Alliance
Times Square Alliance is a nonprofit business improvement organization that manages, promotes, and enhances New York City’s Times Square district.
-
C.
Troop T
Troop T is a specialized division of the New York State Police responsible for law enforcement and safety on the New York State Thruway system.
-
D.
Troop K
Troop K is a regional field division of the New York State Police responsible for law enforcement and public safety in parts of the Hudson Valley region.
-
E.
Troop
Troop is a surname most notably associated with the fictional sea captain Disko Troop from Rudyard Kipling’s novel "Captains Courageous."
- 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_69c6887fcddc8190a5d58908f6dee590 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e557c0108190891ca1be84f21601 |
completed | March 27, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79ca6236c81908a7051bd00d0ca90 |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:42 p.m.