Triple
T31252974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eden (forest cabin) |
E796879
|
entity |
| Predicate | spatialContextInFilm |
P44217
|
FINISHED |
| Object | remote forest area |
—
|
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: remote forest area | Statement: [Eden (forest cabin), spatialContextInFilm, remote forest area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spatialContextInFilm Context triple: [Eden (forest cabin), spatialContextInFilm, remote forest area]
-
A.
cinematicContext
Indicates the relationship in which something is situated within, shaped by, or relevant to the circumstances, style, or conventions of cinema or film.
-
B.
filmingLocationContext
chosen
Indicates the contextual relationship specifying where the filming of an event, scene, or production took place.
-
C.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
D.
placementInFilm
Indicates the specific position or occurrence of something within the sequence or structure of a film.
-
E.
filmLocationFor
Indicates a relationship where a specific place serves as the filming location for a particular film or production.
- 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:12 p.m.