Triple
T37195787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Late August, Early September |
E921586
|
entity |
| Predicate | hasOlivierAssayasFilmographyPosition |
P90338
|
FINISHED |
| Object | follows Irma Vep |
—
|
NE NERFINISHED |
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: follows Irma Vep | Statement: [Late August, Early September, hasOlivierAssayasFilmographyPosition, follows Irma Vep]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOlivierAssayasFilmographyPosition Context triple: [Late August, Early September, hasOlivierAssayasFilmographyPosition, follows Irma Vep]
-
A.
positionInDirectorsCareer
chosen
Indicates the specific point or rank that a work or event occupies within the chronological sequence of a director’s professional career.
-
B.
hasWorkedOnFilmBy
Indicates that one entity has worked on a film that was created, directed, or otherwise authored by another entity.
-
C.
hasFilmographyType
Indicates the type or category of film-related work associated with an entity (e.g., actor, director, producer) within its filmography.
-
D.
workedOnFilmReleasedBy
Indicates that one entity contributed work to a film that was distributed or released by another entity.
-
E.
portrayedInFilmDirectedBy
Indicates that one entity is portrayed as a character in a film that is directed by another specified entity.
- 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_69f76ea313a08190a54404cd1e47da90 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.