Triple
T1747833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Potter film series |
E38374
|
entity |
| Predicate | totalWorldwideBoxOffice |
P1960
|
FINISHED |
| Object | over 7 billion US dollars |
—
|
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 7 billion US dollars | Statement: [Harry Potter film series, totalWorldwideBoxOffice, over 7 billion US dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalWorldwideBoxOffice Context triple: [Harry Potter film series, totalWorldwideBoxOffice, over 7 billion US dollars]
-
A.
boxOfficeGrossUSD
chosen
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
B.
hasBoxOffice
Indicates that an entity (typically a film or performance) has a specific box office revenue amount or record associated with it.
-
C.
boxOfficeStatus
Indicates the commercial performance or financial success status of a film or media release at the box office.
-
D.
usedWorldwide
Indicates that something is utilized or applied across many countries or regions around the world.
-
E.
servedInTheatres
Indicates that a film or performance was publicly exhibited in movie theaters or similar cinema venues.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.