Triple
T10124320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | To Live and Die in L.A. |
E226173
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | John Pankow |
E324407
|
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: John Pankow | Statement: [To Live and Die in L.A., castMember, John Pankow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Pankow Context triple: [To Live and Die in L.A., castMember, John Pankow]
-
A.
John Pankow
chosen
John Pankow is an American actor best known for his role as Ira Buchman on the television sitcom "Mad About You" and for numerous supporting roles in film and theater.
-
B.
James Pankow
James Pankow is an American trombonist, composer, and founding member of the rock band Chicago, known for his influential horn arrangements and songwriting.
-
C.
Bill Pankow
Bill Pankow is an American film editor known for his work on numerous feature films, including crime and thriller dramas.
-
D.
Hal Bidlack
Hal Bidlack is an American political science professor, retired U.S. Air Force officer, and public speaker known for his work in skepticism and secular humanism.
-
E.
Sam Jaffe
Sam Jaffe was an American actor and character performer known for memorable roles in classic films such as "Gunga Din," "The Asphalt Jungle," and "Ben-Hur."
- 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd2ebe4548190a484c145639d92f0 |
completed | April 2, 2026, 2:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc52a4948190a7397c83912f3b15 |
completed | April 5, 2026, 8:55 p.m. |
Created at: March 30, 2026, 9:05 p.m.