Triple
T11638371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The French Renaissance Story |
E276586
|
entity |
| Predicate | isPartOfFilmStructure |
P77503
|
FINISHED |
| Object | one of four parallel stories |
—
|
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: one of four parallel stories | Statement: [The French Renaissance Story, isPartOfFilmStructure, one of four parallel stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfFilmStructure Context triple: [The French Renaissance Story, isPartOfFilmStructure, one of four parallel stories]
-
A.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
B.
basedInFilm
Indicates that something (such as a character, event, or work) is situated, set, or primarily located within the context or universe of a particular film.
-
C.
sequenceInFilm
chosen
Indicates that one entity is a specific sequence or segment that appears within the narrative or structure of a particular film.
-
D.
filmWithinFilm
Indicates that one film is depicted, referenced, or shown as existing within the narrative of another film.
-
E.
isScriptedInPart
Indicates that an entity is partially written, authored, or scripted in the specified language or scripting system, but not entirely.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a25e90c08190b7fb73939a2be3d7 |
completed | April 10, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dd94bdc819091fa2ed33eb31624 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.