Triple
T24766441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manny Pacquiao vs. Oscar De La Hoya |
E619594
|
entity |
| Predicate | gateRevenueApprox |
P151179
|
FINISHED |
| Object | multi-million dollar live gate |
—
|
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: multi-million dollar live gate | Statement: [Manny Pacquiao vs. Oscar De La Hoya, gateRevenueApprox, multi-million dollar live gate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gateRevenueApprox Context triple: [Manny Pacquiao vs. Oscar De La Hoya, gateRevenueApprox, multi-million dollar live gate]
-
A.
hasGateRevenue
chosen
Indicates that an entity receives income from ticket sales or admissions (gate receipts) associated with another entity or event.
-
B.
ticketRevenueModel
Indicates the method or structure by which revenue is generated from ticket sales.
-
C.
boxOfficeAdmissions
Indicates the number of tickets sold for a film or event, reflecting how many people attended via paid admissions.
-
D.
estimatedTheater
Indicates that one entity has calculated or predicted the theater-related value (such as revenue, attendance, or performance metrics) associated with another entity.
-
E.
admissionFee
Indicates the monetary charge required for entry or participation in a place, event, or activity.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a6a5d08190b8f518b3cc13a2e7 |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:28 a.m.