Triple
T6200547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Mantello |
E138617
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Joe Mantello |
E138617
|
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: Joe Mantello | Statement: [Joe Mantello, name, Joe Mantello]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Mantello Context triple: [Joe Mantello, name, Joe Mantello]
-
A.
Joe Mantello
chosen
Joe Mantello is an acclaimed American actor and director, particularly renowned for his work on Broadway in both plays and musicals.
-
B.
Jerry Colonna
Jerry Colonna was an American comedian, actor, and musician best known for his wild-eyed persona and frequent collaborations with Bob Hope in radio, film, and television.
-
C.
Max Silvestri
Max Silvestri is an American stand-up comedian, writer, and actor known for his sharp, observational humor and appearances on various comedy shows and podcasts.
-
D.
Joel McNeely
Joel McNeely is an American composer and conductor best known for his work on film and television scores, including numerous projects for Disney and other major studios.
-
E.
Lou Jacobi
Lou Jacobi was a Canadian-born character actor known for his comedic roles in film, television, and theater, particularly in mid-20th-century Hollywood and Broadway productions.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062547cd48190a2715537b961262e |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d96415c8190b0c5c7f9fd19f5be |
completed | March 24, 2026, 4:05 a.m. |
Created at: March 22, 2026, 4:20 p.m.