Triple
T35478045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plan B |
E1025388
|
entity |
| Predicate | isRoadTripFilm |
P169849
|
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: [Plan B, isRoadTripFilm, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRoadTripFilm Context triple: [Plan B, isRoadTripFilm, true]
-
A.
isFromFilm
Indicates that something (such as a quote, character, scene, or element) originates from or appears in a particular film.
-
B.
tourForFilm
Indicates a relationship where a tour is organized or conducted specifically for the making, promotion, or context of a particular film.
-
C.
isMotionPicture
Indicates that the subject is a motion picture (a film or movie work).
-
D.
roadMovieElements
chosen
Indicates that the work contains key characteristics or motifs typical of a road movie, such as travel-focused narrative, journey-driven character development, and movement across locations.
-
E.
hasCinematicFeature
Indicates that something possesses a specific cinematic characteristic, quality, or element related to film or visual storytelling.
- 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_69f76dfadba0819083456aadcd6864ea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.