Triple
T15312581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Thomas Teller |
E366073
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | John Diehl |
—
|
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: John Diehl | Statement: [John Thomas Teller, portrayedBy, John Diehl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Diehl Context triple: [John Thomas Teller, portrayedBy, John Diehl]
-
A.
John Diehl
chosen
John Diehl is an American character actor best known for his role as Detective Larry Zito on the 1980s television series "Miami Vice."
-
B.
Frank Doelger
Frank Doelger is a television producer best known for his work on the acclaimed HBO fantasy series "Game of Thrones."
-
C.
William Diehl
William Diehl was an American novelist best known for his gritty, suspenseful legal and crime thrillers.
-
D.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
-
E.
John Kiffmeyer
John Kiffmeyer is an American drummer best known for being the original drummer of the punk rock band Green Day during their early years.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03cd2d5a88190aead748920f93d47 |
completed | April 16, 2026, 1:35 a.m. |
Created at: April 10, 2026, 3:16 a.m.