Triple
T33851415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outward Bound |
E867632
|
entity |
| Predicate | isBlackAndWhiteInFilmAdaptations |
P87540
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Outward Bound, isBlackAndWhiteInFilmAdaptations, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBlackAndWhiteInFilmAdaptations Context triple: [Outward Bound, isBlackAndWhiteInFilmAdaptations, true]
-
A.
playedInBlackAndWhiteOrColorFilm
Indicates that the subject participated in a film, regardless of whether it was produced in black-and-white or in color.
-
B.
blackAndWhiteFilmCharacter
chosen
Indicates that a character appears in, is associated with, or belongs to a black-and-white film.
-
C.
isBlackAndWhiteEpisodeOf
Indicates that an episode is a black-and-white version belonging to a particular series or show.
-
D.
inFilmAdaptation
Indicates that one work or element appears within, or is incorporated into, a film adaptation of another work.
-
E.
fromFilmAdaptation
Indicates that something originates from, or is derived from, a film adaptation of another work.
- 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_69f349937b648190a34ada70f6a2b534 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70073e67c8190aa5b578cafed96db |
completed | May 3, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:47 a.m.