Triple
T10324087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antlers Holst |
E242714
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Michael Wincott |
E343363
|
NE 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: Michael Wincott | Statement: [Antlers Holst, portrayedBy, Michael Wincott]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Wincott Context triple: [Antlers Holst, portrayedBy, Michael Wincott]
-
A.
Michael Wincott
chosen
Michael Wincott is a Canadian character actor known for his distinctive raspy voice and memorable villainous roles in films such as The Crow, Robin Hood: Prince of Thieves, and Nope.
-
B.
Matthew Weisman
Matthew Weisman is a screenwriter best known for co-writing the 1985 action film "Commando" starring Arnold Schwarzenegger.
-
C.
Michael Haussman
Michael Haussman is an American director and filmmaker best known for his work on high-profile music videos and commercials.
-
D.
Michael Filerman
Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
-
E.
Matthew Salsberg
Matthew Salsberg is a television writer and producer best known for his work on the dark comedy series "Weeds."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6ce683c8190bf5385dd04bf2de8 |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb028c0788190ae8d6750f2f9634e |
completed | April 14, 2026, 9:22 p.m. |
Created at: April 6, 2026, 11:51 a.m.