Triple
T34858369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Journey to a Star |
E1004787
|
entity |
| Predicate | filmFormatOfIntroduction |
P86894
|
FINISHED |
| Object | Technicolor |
—
|
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: Technicolor | Statement: [A Journey to a Star, filmFormatOfIntroduction, Technicolor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmFormatOfIntroduction Context triple: [A Journey to a Star, filmFormatOfIntroduction, Technicolor]
-
A.
appearsInFilmFormat
Indicates that something is presented or occurs within a specific film format or medium of cinematic presentation.
-
B.
usesFilmFormat
chosen
Indicates that one entity employs or is recorded in a particular film format associated with the other entity.
-
C.
introducedFilmFormatToMassMarket
Indicates that an entity was responsible for bringing a particular film format into widespread commercial use among the general public.
-
D.
filmAdaptationFormat
Indicates the specific medium or format (e.g., feature film, TV movie, short film) in which a work has been adapted into a film.
-
E.
cinematicForm
Indicates that something is expressed, structured, or realized through the techniques, conventions, or medium of cinema or film.
- 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_69f76dba76f0819090643cba102c41ec |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.