Triple
T31446284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Senate seat from New York |
E802194
|
entity |
| Predicate | compensationDeterminedBy |
P125642
|
FINISHED |
| Object | United States Congress |
—
|
NE NERFINISHED |
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: United States Congress | Statement: [United States Senate seat from New York, compensationDeterminedBy, United States Congress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compensationDeterminedBy Context triple: [United States Senate seat from New York, compensationDeterminedBy, United States Congress]
-
A.
compensationModel
Indicates the type or structure of payment or rewards provided in exchange for work, services, or performance.
-
B.
basisOfWageDetermination
Indicates the factor or criteria used to determine the amount or structure of a wage.
-
C.
compensationSetBy
chosen
Indicates that one party determines or establishes the compensation or pay level for another party.
-
D.
compensationCategory
Indicates the type or classification of compensation associated with an entity, such as how or in what form payment or remuneration is provided.
-
E.
compensationRate
Indicates the rate or amount of payment provided in exchange for a specified unit of work, time, or service.
- 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_69f348c5a6bc819092a557e95438976f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 30, 2026, 9:09 p.m.