Triple
T28902471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blade Runner Partnership |
E732984
|
entity |
| Predicate | workTypeFinanced |
P1366
|
FINISHED |
| Object | feature film |
—
|
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: feature film | Statement: [Blade Runner Partnership, workTypeFinanced, feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workTypeFinanced Context triple: [Blade Runner Partnership, workTypeFinanced, feature film]
-
A.
associatedWorkType
Indicates the type or category of work with which an entity is associated (e.g., publication, artwork, performance).
-
B.
typeOfWork
chosen
Indicates the kind or category of work associated with or performed by an entity.
-
C.
workFor
Indicates that one entity is employed by or performs work under the authority or direction of another entity.
-
D.
appliedWork
Indicates that an entity has put effort, skill, or labor into performing or producing a particular work or task.
-
E.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65ad890b88190a1a2214e5da01585 |
completed | May 2, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69f6576487e081908d802f1caf59c423 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 8:04 a.m.