Triple
T155718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bodyguard |
E3174
|
entity |
| Predicate | boxOffice |
P3427
|
FINISHED |
| Object | over 400 million USD worldwide |
—
|
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: over 400 million USD worldwide | Statement: [The Bodyguard, boxOffice, over 400 million USD worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boxOffice Context triple: [The Bodyguard, boxOffice, over 400 million USD worldwide]
-
A.
boxOfficeGrossUSD
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
B.
hasBoxOffice
chosen
Indicates that an entity (typically a film or performance) has a specific box office revenue amount or record associated with it.
-
C.
hasNumberOfTheatres
Indicates the quantity of theatres associated with or present in a given entity.
-
D.
worldPremiereDate
Indicates the date on which a work (such as a film, play, or musical piece) is first publicly premiered anywhere in the world.
-
E.
theatricalReleaseDateUS
Indicates the calendar date on which a work was first released theatrically in the United States.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2565ded588190a27319aaa0130b4f |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.