Triple
T14358569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Perfect Guy |
E356035
|
entity |
| Predicate | boxOfficeOpeningWeekendUS |
P113916
|
FINISHED |
| Object | 26000000 USD (approximate) |
—
|
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: 26000000 USD (approximate) | Statement: [The Perfect Guy, boxOfficeOpeningWeekendUS, 26000000 USD (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boxOfficeOpeningWeekendUS Context triple: [The Perfect Guy, boxOfficeOpeningWeekendUS, 26000000 USD (approximate)]
-
A.
boxOfficeGrossUSD
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
B.
boxOfficeStatus
Indicates the commercial performance or financial success status of a film or media release at the box office.
-
C.
countryBoxOfficeGrossUSD
Indicates the total box office revenue, in U.S. dollars, that a work earned within a specific country.
-
D.
hasBoxOffice
Indicates that an entity (typically a film or performance) has a specific box office revenue amount or record associated with it.
-
E.
hasBoxOfficeType
Indicates the classification of a work’s box office performance or revenue category (e.g., type or scale of its box office results).
- F. None of above. chosen
Provenance (4 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f52ca7881908704eef20228aed3 |
completed | April 14, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69de2a9958e881909d03ac03f135163e |
completed | April 14, 2026, 11:52 a.m. |
| PDg | Predicate description generation | batch_69de2e8a40e4819080240c874da1842c |
completed | April 14, 2026, 12:09 p.m. |
Created at: April 10, 2026, 1:15 a.m.