Triple
T32469423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bride of Chucky (film score) |
E829807
|
entity |
| Predicate | filmMainCharacters |
P39597
|
FINISHED |
| Object | Chucky |
—
|
NE NERFINISHED |
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: Chucky | Statement: [Bride of Chucky (film score), filmMainCharacters, Chucky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmMainCharacters Context triple: [Bride of Chucky (film score), filmMainCharacters, Chucky]
-
A.
filmCharacterOf
Indicates that a person or character is a character appearing in a specified film.
-
B.
filmLeadCharacter
Indicates that a person or character serves as the primary or central protagonist in a film.
-
C.
mainCharactersAre
chosen
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
D.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
-
E.
associatedCharacters
Indicates that two or more characters are linked or connected through some relationship, involvement, or relevance to each other.
- 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_69f3491ee87c81908cbf5890079c2af6 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c35400148190952f711f098ae7a3 |
completed | May 3, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69f6ba700a708190ab6db62791e43774 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:57 a.m.