Triple
T6220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York State Senator |
E124
|
entity |
| Predicate | officeType |
P303
|
FINISHED |
| Object | legislative office |
—
|
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: legislative office | Statement: [New York State Senator, officeType, legislative office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeType Context triple: [New York State Senator, officeType, legislative office]
-
A.
leftOffice
Indicates that an entity ceased holding or performing the duties of a particular office or position.
-
B.
typeOfContract
Indicates the specific kind or category of contractual agreement that applies between the related entities.
-
C.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
D.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
E.
employer
Indicates a relationship where one entity hires, pays, and oversees the work of another 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2421836f08190b54fc40edeb1a96b |
completed | Feb. 28, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69a23fe064c881909496fd0e6b0e18d7 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.