Triple
T26337005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brother Carl |
E662547
|
entity |
| Predicate | hasMiseEnScene |
P41012
|
FINISHED |
| Object | austere |
—
|
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: austere | Statement: [Brother Carl, hasMiseEnScene, austere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMiseEnScene Context triple: [Brother Carl, hasMiseEnScene, austere]
-
A.
hasCinematicFeature
Indicates that something possesses a specific cinematic characteristic, quality, or element related to film or visual storytelling.
-
B.
hasBehindTheScenesFilm
Indicates that one work includes or is associated with a behind-the-scenes film documenting its creation or production process.
-
C.
hasDanceSceneWith
Indicates that two entities participate together in a dance scene within the same context or work.
-
D.
hasFilmStyle
chosen
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
-
E.
hasFilmStructure
Indicates that one entity possesses or is organized according to the narrative or formal structure of a 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_69ee81304194819092e20e0fae3aee07 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 26, 2026, 10:36 p.m.