Triple
T22496208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bluntman and Chronic |
E556146
|
entity |
| Predicate | hasFilmAdaptationInFiction |
P131519
|
FINISHED |
| Object | Bluntman and Chronic movie |
—
|
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: Bluntman and Chronic movie | Statement: [Bluntman and Chronic, hasFilmAdaptationInFiction, Bluntman and Chronic movie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmAdaptationInFiction Context triple: [Bluntman and Chronic, hasFilmAdaptationInFiction, Bluntman and Chronic movie]
-
A.
hasPreviousFilmAdaptation
Indicates that a work has been adapted into a film before the current or referenced adaptation.
-
B.
hasGraphicNovelAdaptation
Indicates that a work has been adapted into a graphic novel format.
-
C.
isTelevisionAdaptationOf
Indicates that a television show is an adaptation derived from the story, characters, or content of another original work.
-
D.
inFilmAdaptation
Indicates that one work or element appears within, or is incorporated into, a film adaptation of another work.
-
E.
hasFilmAdaptationTitle
chosen
Indicates that a creative work has a film adaptation whose title is given by the related value.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15cb2644c819094864bd88bcebcbd |
completed | April 29, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:50 p.m.