Triple
T10751122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Brink's Job |
E253572
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Peter Boyle |
E162392
|
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 Boyle | Statement: [The Brink's Job, starredActor, Peter Boyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Boyle Context triple: [The Brink's Job, starredActor, Peter Boyle]
-
A.
Peter Boyle
chosen
Peter Boyle was an American character actor best known for his roles in films like "Young Frankenstein" and "Taxi Driver" and the TV series "Everybody Loves Raymond."
-
B.
Peter Boyle
Peter Boyle is a film editor known for his work on acclaimed movies such as "The Hours."
-
C.
Harold Gould
Harold Gould was an American character actor best known for his prolific work in film and television from the 1960s through the 1990s, including memorable roles in projects like "The Sting" and the TV series "The Golden Girls."
-
D.
Robert Walter
Robert Walter is a British Conservative politician who served as a Member of Parliament, notably representing the North Dorset constituency for many years.
-
E.
Alan Baxter
Alan Baxter was an American character actor known for his roles in mid-20th-century film and television, often portraying tough or villainous figures.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71dc0ad188190b747bf9d10cf5de5 |
completed | April 9, 2026, 3:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb0a03a1481908edb933b1613a027 |
completed | April 14, 2026, 9:24 p.m. |
Created at: April 8, 2026, 9:15 p.m.