Triple
T13694337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | This Christmas |
E328344
|
entity |
| Predicate | hasBoxOfficePerformance |
P11911
|
FINISHED |
| Object | commercially successful |
—
|
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: commercially successful | Statement: [This Christmas, hasBoxOfficePerformance, commercially successful]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoxOfficePerformance Context triple: [This Christmas, hasBoxOfficePerformance, commercially successful]
-
A.
hasBoxOffice
Indicates that an entity (typically a film or performance) has a specific box office revenue amount or record associated with it.
-
B.
hasBoxOfficeType
Indicates the classification of a work’s box office performance or revenue category (e.g., type or scale of its box office results).
-
C.
boxOfficeStatus
chosen
Indicates the commercial performance or financial success status of a film or media release at the box office.
-
D.
boxOfficeGrossUSD
Indicates the total amount of money an entity earned at the box office, expressed in U.S. dollars.
-
E.
hasCommercialPerformance
Indicates that an entity’s success or outcome is characterized in terms of its performance in the commercial or market context (e.g., sales, revenue, or profitability).
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8757b648190a26181efbad09a43 |
completed | April 12, 2026, 4:29 p.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:54 p.m.