Triple
T15996013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Levine |
E387966
|
entity |
| Predicate | hasDirectedFeatureFilm |
P121216
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Jonathan Levine, hasDirectedFeatureFilm, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirectedFeatureFilm Context triple: [Jonathan Levine, hasDirectedFeatureFilm, Yes]
-
A.
producedFilm
Indicates that one entity served as the producer (or production company) responsible for making or financing the creation of a particular film.
-
B.
portrayedInFilmDirectedBy
Indicates that one entity is portrayed as a character in a film that is directed by another specified entity.
-
C.
hasWorkedOnFilmBy
Indicates that one entity has worked on a film that was created, directed, or otherwise authored by another entity.
-
D.
hasNotableFilm
Indicates that an entity is associated with a film that is considered significant, well-known, or particularly noteworthy.
-
E.
producedFilmStarring
Indicates that a person or company produced a film in which a specified actor or set of actors starred.
- F. None of above. chosen
Provenance (4 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4e871c819082d7b1c1eaf5b4fe |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:55 a.m.