Triple
T1442836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York State Police |
E31111
|
entity |
| Predicate | hasTypeOfOfficer |
P16376
|
FINISHED |
| Object | uniformed trooper |
—
|
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: uniformed trooper | Statement: [New York State Police, hasTypeOfOfficer, uniformed trooper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfOfficer Context triple: [New York State Police, hasTypeOfOfficer, uniformed trooper]
-
A.
isOfficerOf
Indicates that one entity holds an official position, role, or office within another entity (such as an organization, group, or institution).
-
B.
hasOfficeHolderType
chosen
Indicates that an office or position is associated with a specific type or category of office holder (e.g., elected official, appointed official).
-
C.
officersAre
Indicates that certain individuals hold the role or position of officers within a specified group, organization, or context.
-
D.
isSeniorLegalOfficerFor
Indicates that one person holds a senior legal authority or leadership role with primary legal responsibility for another entity (such as an organization, unit, or individual).
-
E.
hasOfficeType
Indicates that an entity’s office is classified as a specific type or category of office.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c55714588190a95b4f677c21cbaa |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c47a840c819083307a65c027a19e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.