Triple
T7560235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Wounds |
E178774
|
entity |
| Predicate | starsActor |
P5563
|
FINISHED |
| Object | Peter Macon |
E34010
|
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: Peter Macon | Statement: [Old Wounds, starsActor, Peter Macon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Macon Context triple: [Old Wounds, starsActor, Peter Macon]
-
A.
Peter Macon
chosen
Peter Macon is an American actor best known for playing the Moclan officer Lt. Cmdr. Bortus on the science fiction comedy-drama series "The Orville."
-
B.
Lewis Pullman
Lewis Pullman is an American actor known for roles in films such as "Top Gun: Maverick," "Bad Times at the El Royale," and "The Strangers: Prey at Night."
-
C.
Stephen Dillane
Stephen Dillane is a British actor known for his nuanced performances in film, television, and theatre, including roles in "Game of Thrones," "The Tunnel," and "The Hours."
-
D.
Richard Gant
Richard Gant is an American character actor known for his roles in film and television, often portraying authoritative or tough-minded figures.
-
E.
Ian Hanmore
Ian Hanmore is a Scottish character actor known for his work in British film and television, including roles in series like Game of Thrones and Doctor Who.
- 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_69c69f2f80288190b95cceb4da92ab2b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8dd96488190b4cca25ae8f7f95c |
completed | March 27, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856cc869081909555ae03dec52288 |
completed | March 28, 2026, 10:31 p.m. |
Created at: March 27, 2026, 3:50 p.m.