Triple
T789718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York State Assembly |
E16883
|
entity |
| Predicate | salaryOfMembers |
P3415
|
FINISHED |
| Object | $142000 per year |
—
|
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: $142000 per year | Statement: [New York State Assembly, salaryOfMembers, $142000 per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: salaryOfMembers Context triple: [New York State Assembly, salaryOfMembers, $142000 per year]
-
A.
salary
chosen
Indicates the amount of monetary compensation an entity receives, typically on a regular basis, for work or services performed.
-
B.
salaryType
Indicates the classification or structure of compensation associated with an entity, such as whether pay is salaried, hourly, commission-based, or another type.
-
C.
payGrade
Indicates the level or category of compensation assigned to an entity, typically reflecting its rank, role, or seniority in a pay structure.
-
D.
eligibleMembers
Indicates that certain entities meet the required criteria or conditions to be considered eligible members of a specified group or category.
-
E.
totalMembershipApprox
Indicates an approximate total count of members associated with an 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7841b0c8190859ecd247e32c6ec |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50ef72c819084ffe9f31dbd0262 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:38 p.m.