Triple
T19829546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rip Wheeler |
E476418
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Cole Hauser |
—
|
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: Cole Hauser | Statement: [Rip Wheeler, portrayedBy, Cole Hauser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cole Hauser Context triple: [Rip Wheeler, portrayedBy, Cole Hauser]
-
A.
Cole Hauser
chosen
Cole Hauser is an American actor known for his tough, authoritative roles in films like "Dazed and Confused," "Pitch Black," and "2 Fast 2 Furious," as well as the TV series "Yellowstone."
-
B.
Dolph Lundgren
Dolph Lundgren is a Swedish actor, director, and martial artist best known for his tough-guy roles in action films such as "Rocky IV" and "The Expendables" series.
-
C.
Tim Matheson
Tim Matheson is an American actor and director best known for his roles in films like "National Lampoon's Animal House" and numerous television series.
-
D.
Jean-Claude Van Damme
Jean-Claude Van Damme is a Belgian martial artist and action film star best known for movies like "Bloodsport," "Kickboxer," and "Universal Soldier."
-
E.
Adam LaVorgna
Adam LaVorgna is an American actor best known for his roles in the television series "7th Heaven" and films such as "The Beautician and the Beast."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656ccd3748190adeaed9a431f8979 |
completed | April 20, 2026, 4:39 p.m. |
Created at: April 10, 2026, 1:50 p.m.