Triple
T9234231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hotel du Nord |
E221894
|
entity |
| Predicate | hasFilmMovement |
P12614
|
FINISHED |
| Object | poetic realism |
—
|
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: poetic realism | Statement: [Hotel du Nord, hasFilmMovement, poetic realism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmMovement Context triple: [Hotel du Nord, hasFilmMovement, poetic realism]
-
A.
hasNotableFilm
Indicates that an entity is associated with a film that is considered significant, well-known, or particularly noteworthy.
-
B.
filmMovement
chosen
Indicates the cinematic movement or stylistic school with which a film is associated.
-
C.
hasInteractiveFilm
Indicates that an entity is associated with, offers, or features an interactive film experience.
-
D.
hasFilmStyle
Indicates that a film exhibits or is characterized by a particular cinematic style or aesthetic approach.
-
E.
endedWithFilm
Indicates that an event, series, or process concluded with the showing, release, or occurrence of a particular 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_69ca83ed628c8190bc02d641e57f097f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccee1baa3c8190870d1e850ccab1e0 |
completed | April 1, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_69cc7a3daeb481908b0abde3fbc1f1f0 |
completed | April 1, 2026, 1:51 a.m. |
Created at: March 30, 2026, 7:29 p.m.