Triple
T23514507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Princess Diaries |
E574318
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Mario Iscovich |
—
|
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: Mario Iscovich | Statement: [The Princess Diaries, producer, Mario Iscovich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mario Iscovich Context triple: [The Princess Diaries, producer, Mario Iscovich]
-
A.
Mario Iscovich
chosen
Mario Iscovich is a film producer best known for his work on popular Hollywood movies such as "The Princess Diaries."
-
B.
George Kralovansky
George Kralovansky is a television producer best known for his executive production work on the live law-enforcement reality series "Live PD."
-
C.
Mario Nascimbene
Mario Nascimbene was an Italian film composer renowned for his innovative scores for both European cinema and major Hollywood productions in the mid-20th century.
-
D.
Richard Kovacevich
Richard Kovacevich is an American banker best known for serving as CEO and chairman of Wells Fargo.
-
E.
Martin Pasko
Martin Pasko was an American comic book and television writer best known for his work on DC Comics characters, particularly Superman and Batman, and for contributing to various animated series.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa80d9048190ab735dddd301feb4 |
completed | April 29, 2026, 6:51 a.m. |
Created at: April 17, 2026, 6:08 p.m.