Triple
T18198033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Picerni |
E435710
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Paul Picerni |
—
|
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: Paul Picerni | Statement: [Paul Picerni, name, Paul Picerni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Picerni Context triple: [Paul Picerni, name, Paul Picerni]
-
A.
Paul Picerni
chosen
Paul Picerni was an American film and television actor best known for his role as Agent Lee Hobson on the TV series "The Untouchables."
-
B.
Paul Fabrini
Paul Fabrini is the tough, hardworking truck driver protagonist of the 1940 film noir drama "They Drive by Night."
-
C.
Jacques Cruppi
Jacques Cruppi was a French lawyer, politician, and art patron active in the late 19th and early 20th centuries.
-
D.
Jean Leonetti
Jean Leonetti is a French politician and physician known for his work on end-of-life legislation and his long-standing role in center-right national politics.
-
E.
Paul Gambaccini
Paul Gambaccini is a British-American radio and television presenter and music historian best known for his long-running work on BBC music programmes.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d47f1c819082eec59492497797 |
completed | April 19, 2026, 2:04 p.m. |
Created at: April 10, 2026, 10:31 a.m.