Triple
T21077019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Affinity Gaming |
E519261
|
entity |
| Predicate | coreRevenueSource |
P7220
|
FINISHED |
| Object | gaming 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: gaming revenue | Statement: [Affinity Gaming, coreRevenueSource, gaming revenue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreRevenueSource Context triple: [Affinity Gaming, coreRevenueSource, gaming revenue]
-
A.
revenueSources
Indicates the relationship identifying where an entity’s revenue comes from or the different streams that generate its income.
-
B.
majorRevenueSource
chosen
Indicates that one entity serves as the primary or dominant source of revenue for another entity.
-
C.
revenueSourceShift
Indicates a change in where or how an entity primarily generates its revenue, such as moving from one main income stream or business model to another.
-
D.
revenue
Indicates the amount of income generated by an entity from its business activities or operations over a specified period.
-
E.
revenueUse
Indicates how generated revenue is allocated, spent, or applied toward specific purposes or activities.
- 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_69e0b506e59c8190849b71ed07929215 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e702d77b8081908ecfb05ab391fd39 |
completed | April 21, 2026, 4:53 a.m. |
| PD | Predicate disambiguation | batch_69e5dbfcd5e881908f1e4e0d2d237856 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:49 p.m.