Triple
T12476678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borat: Cultural Learnings of America for Make Benefit Glorious Nation of Kazakhstan |
E298191
|
entity |
| Predicate | approximateBoxOfficeGrossUSD |
P1960
|
FINISHED |
| Object | 260000000 |
—
|
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: 260000000 | Statement: [Borat: Cultural Learnings of America for Make Benefit Glorious Nation of Kazakhstan, approximateBoxOfficeGrossUSD, 260000000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateBoxOfficeGrossUSD Context triple: [Borat: Cultural Learnings of America for Make Benefit Glorious Nation of Kazakhstan, approximateBoxOfficeGrossUSD, 260000000]
-
A.
boxOfficeGrossUSD
chosen
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
B.
countryBoxOfficeGrossUSD
Indicates the total box office revenue, in U.S. dollars, that a work earned within a specific country.
-
C.
currencyOfBoxOfficeGrossWorldwide
Indicates the currency in which the worldwide box office gross amount is denominated.
-
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.
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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.