Triple
T23480555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Hays as Ted Striker |
E570392
|
entity |
| Predicate | reprisesRoleIn |
P46748
|
FINISHED |
| Object | Airplane II: The Sequel |
—
|
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: Airplane II: The Sequel | Statement: [Robert Hays as Ted Striker, reprisesRoleIn, Airplane II: The Sequel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reprisesRoleIn Context triple: [Robert Hays as Ted Striker, reprisesRoleIn, Airplane II: The Sequel]
-
A.
playedEarlyRoleIn
Indicates that one entity contributed significantly to the initial or formative stages of another entity’s development, success, or emergence.
-
B.
featuresActorInMultipleRoles
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
C.
playedRoleIn
Indicates that an entity performed or assumed a specific role or character within a particular event, production, or context.
-
D.
reprisePerformersInStory
chosen
Indicates that certain performers reappear in the same roles or capacities within a subsequent part or version of the story.
-
E.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
- 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a75002008190b02fbffd94e5e8b1 |
completed | April 29, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:03 p.m.