Triple
T6278777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claireece "Precious" Jones |
E140726
|
entity |
| Predicate | filmAdaptationOfCharacterFrom |
P66482
|
FINISHED |
| Object | Push |
—
|
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: Push | Statement: [Claireece "Precious" Jones, filmAdaptationOfCharacterFrom, Push]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmAdaptationOfCharacterFrom Context triple: [Claireece "Precious" Jones, filmAdaptationOfCharacterFrom, Push]
-
A.
inFilmAdaptation
Indicates that one work or element appears within, or is incorporated into, a film adaptation of another work.
-
B.
filmBasedOn
Indicates that a film is adapted from or derived from the story, characters, or events of another work.
-
C.
filmAdaptationEvaPerformer
Indicates that the subject is a performer who played the character Eva in a film adaptation of the referenced work.
-
D.
filmAdaptationStudio
Indicates that a particular studio is responsible for producing or creating the film adaptation of a work.
-
E.
filmCharacterVersionOf
chosen
Indicates that one character is a specific film adaptation or portrayal of another character originating from a different version or medium.
- 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_69c008cc158881908df6ec94a911c736 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063dc55d48190b5ed48a50f3a742e |
completed | March 22, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69c05608a5608190b22a1fdc4060470d |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:26 p.m.