Triple
T36252366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ropin' the Wind |
E891836
|
entity |
| Predicate | approximateSalesWorldwide |
P22826
|
FINISHED |
| Object | over 14 million copies |
—
|
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 14 million copies | Statement: [Ropin' the Wind, approximateSalesWorldwide, over 14 million copies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateSalesWorldwide Context triple: [Ropin' the Wind, approximateSalesWorldwide, over 14 million copies]
-
A.
currencyOfBoxOfficeGrossWorldwide
Indicates the currency in which the worldwide box office gross amount is denominated.
-
B.
boxOfficeGrossUSD
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
C.
boxOfficeWorldwideINR
Indicates the total worldwide box office revenue of a work, expressed in Indian Rupees (INR).
-
D.
boxOfficeInternationalUSD
Indicates the amount of money a work earned in international (non-domestic) box offices, measured in U.S. dollars.
-
E.
salesWorldwide
chosen
Indicates a relationship where an entity’s sales figures or activities are measured, reported, or occur across multiple countries or global markets.
- 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_69f76e4599108190811532e707d6bc2c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff7fc835f08190afd1f8129b7a62a2 |
completed | May 9, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69ff7f2e99ac8190ba372a1358a05a30 |
completed | May 9, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:09 p.m.