Triple
T30555435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunn (1967 film) |
E777682
|
entity |
| Predicate | featuresActorReprisingRole |
P105074
|
FINISHED |
| Object | Craig Stevens |
—
|
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: Craig Stevens | Statement: [Gunn (1967 film), featuresActorReprisingRole, Craig Stevens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresActorReprisingRole Context triple: [Gunn (1967 film), featuresActorReprisingRole, Craig Stevens]
-
A.
featuresActorInMultipleRoles
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
B.
creditedRoleOf
Indicates that a particular role or position is formally acknowledged as being held or performed by a specific entity in a credit or attribution context.
-
C.
hasPortrayedRole
Indicates that an entity has performed or depicted a specific role or character, typically in a work such as a film, play, or television show.
-
D.
alsoPortrayedBy
chosen
Indicates that the same role or character is portrayed by an additional, different performer or actor.
-
E.
hasPortrayedPersonRole
Indicates that an entity has performed or held a specific role in portraying a particular person (e.g., in a film, play, or other representation).
- 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_69f2249e19108190a458ab446096bf22 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a000be59ad88190a6aa3a42c097796d |
completed | May 10, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_6a000ab6e9bc81908300b81d004e5921 |
completed | May 10, 2026, 4:33 a.m. |
Created at: April 29, 2026, 8:20 p.m.