Triple
T28718182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Demonic |
E730017
|
entity |
| Predicate | hasDirectorFilmographyPosition |
P120732
|
FINISHED |
| Object | first horror feature by Neill Blomkamp |
—
|
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: first horror feature by Neill Blomkamp | Statement: [Demonic, hasDirectorFilmographyPosition, first horror feature by Neill Blomkamp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirectorFilmographyPosition Context triple: [Demonic, hasDirectorFilmographyPosition, first horror feature by Neill Blomkamp]
-
A.
hasDirectorInKeyWork
Indicates that a director is associated with a key or primary work of an entity (such as a film, series, or major production).
-
B.
hasDirectorOfWork
Indicates that an entity has a specific person or organization serving as the director responsible for overseeing its work or project.
-
C.
hasDirectorStar
Indicates that a person both directed and starred in the same work (e.g., film, show, or production).
-
D.
hasWorkedOnFilmBy
Indicates that one entity has worked on a film that was created, directed, or otherwise authored by another entity.
-
E.
hasFilmographyType
chosen
Indicates the type or category of film-related work associated with an entity (e.g., actor, director, producer) within its filmography.
- 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: April 28, 2026, 5:52 a.m.