Triple
T27208579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bajirao Mastani |
E683938
|
entity |
| Predicate | boxOfficeWorldwideINR |
P162253
|
FINISHED |
| Object | 356 crore |
—
|
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: 356 crore | Statement: [Bajirao Mastani, boxOfficeWorldwideINR, 356 crore]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boxOfficeWorldwideINR Context triple: [Bajirao Mastani, boxOfficeWorldwideINR, 356 crore]
-
A.
boxOfficeInternationalUSD
Indicates the amount of money a work earned in international (non-domestic) box offices, measured in U.S. dollars.
-
B.
currencyOfBoxOfficeGrossWorldwide
Indicates the currency in which the worldwide box office gross amount is denominated.
-
C.
countryBoxOfficeGrossUSD
Indicates the total box office revenue, in U.S. dollars, that a work earned within a specific country.
-
D.
boxOfficeGrossUSD
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
E.
boxOfficeStatus
Indicates the commercial performance or financial success status of a film or media release at the box office.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f625e6cd708190aea9dc220df25717 |
completed | May 2, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f622a8fe7c819096e8a43db263a423 |
completed | May 2, 2026, 4:13 p.m. |
Created at: April 27, 2026, 9:38 a.m.