Triple
T12667410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Hanks as Colonel Tom Parker |
E302591
|
entity |
| Predicate | associatedActorCoStar |
P14987
|
FINISHED |
| Object | Austin Butler as Elvis Presley |
—
|
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: Austin Butler as Elvis Presley | Statement: [Tom Hanks as Colonel Tom Parker, associatedActorCoStar, Austin Butler as Elvis Presley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedActorCoStar Context triple: [Tom Hanks as Colonel Tom Parker, associatedActorCoStar, Austin Butler as Elvis Presley]
-
A.
directorSpouseInCast
Indicates that a film’s director is married to someone who appears as a cast member in that same film.
-
B.
playedInEnsembleWith
Indicates that one entity has performed together with another as members of the same musical ensemble or group.
-
C.
co-star
chosen
Indicates that two or more performers appear together in the same production, sharing significant acting roles.
-
D.
alsoPortrayedBy
Indicates that the same role or character is portrayed by an additional, different performer or actor.
-
E.
hasTwinActors
Indicates that two or more actors share a twin relationship, typically portraying twin characters or being treated as twins within a given 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.