Triple
T7149487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NY6 |
E166655
|
entity |
| Predicate | revenueSignificance |
P2342
|
FINISHED |
| Object | major source of CFP revenue |
—
|
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: major source of CFP revenue | Statement: [NY6, revenueSignificance, major source of CFP revenue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revenueSignificance Context triple: [NY6, revenueSignificance, major source of CFP revenue]
-
A.
revenueLevel
chosen
Indicates the relative amount or tier of revenue associated with an entity or activity.
-
B.
revenue
Indicates the amount of income generated by an entity from its business activities or operations over a specified period.
-
C.
revenueUse
Indicates how generated revenue is allocated, spent, or applied toward specific purposes or activities.
-
D.
majorRevenueSource
Indicates that one entity serves as the primary or dominant source of revenue for another entity.
-
E.
commercialSignificance
Indicates that something has notable economic or business importance, value, or impact in a commercial context.
- 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_69c68886779c8190a8e3fbabffe68253 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7f130e08190bc5ca99f90f9de92 |
completed | March 27, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69c6e1caf4e48190b47bb398a3c1554d |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:46 p.m.