Triple
T16295426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Police Story |
E395633
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Joseph Wambaugh |
E824125
|
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: Joseph Wambaugh | Statement: [Police Story, creator, Joseph Wambaugh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joseph Wambaugh Context triple: [Police Story, creator, Joseph Wambaugh]
-
A.
Joseph Wambaugh
chosen
Joseph Wambaugh is an American author and former LAPD detective best known for his influential true-crime and police procedural books.
-
B.
J. Peter Robinson
J. Peter Robinson is a British composer, arranger, and keyboardist known for his film and television scores as well as his work in rock and jazz fusion.
-
C.
Gerry McGee
Gerry McGee was an American guitarist best known for his long tenure with the influential instrumental rock band The Ventures.
-
D.
John Forsyth
John Forsyth was a 19th-century American politician and statesman who served as U.S. Secretary of State, governor of Georgia, and a prominent member of Congress.
-
E.
David Nobbs
David Nobbs was a British comedy writer and novelist best known for his sharp, character-driven humor and influential work in television sitcoms and comic fiction.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2d08108190bab1b3325923af1d |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f9965b8819080278ccef15288aa |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.