Triple
T10926302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zoe Ever After |
E258076
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Erica Montolfo-Bura |
E904916
|
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: Erica Montolfo-Bura | Statement: [Zoe Ever After, executiveProducer, Erica Montolfo-Bura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erica Montolfo-Bura Context triple: [Zoe Ever After, executiveProducer, Erica Montolfo-Bura]
-
A.
Erica Montolfo-Bura
chosen
Erica Montolfo-Bura is a television writer and producer best known for co-creating and developing the BET sitcom "Zoe Ever After."
-
B.
Tharita Cesaroni
Tharita Cesaroni is an Italian film producer and cinematographer known for her work behind the camera and for being married to actor Dermot Mulroney.
-
C.
Mara Carfagna
Mara Carfagna is an Italian politician and former television showgirl who has served as a prominent minister and parliamentarian in center-right governments.
-
D.
Marisa Polvino
Marisa Polvino is a film producer known for her work on major feature films, including the 2014 science fiction movie "Transcendence."
-
E.
Alicia Cazzaniga
Alicia Cazzaniga is an Argentine architect best known for co-designing the iconic modernist building of the National Library of Argentina in Buenos Aires.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7709165188190aa30dd08deddade4 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d4f9518819091f7e02ad5f63ab3 |
completed | April 19, 2026, 1:18 a.m. |
Created at: April 8, 2026, 9:22 p.m.