Triple
T14102554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friday (film) |
E339419
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Patricia Charbonnet |
E557856
|
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: Patricia Charbonnet | Statement: [Friday (film), producer, Patricia Charbonnet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patricia Charbonnet Context triple: [Friday (film), producer, Patricia Charbonnet]
-
A.
Patricia Charbonnet
chosen
Patricia Charbonnet is a film producer best known for her work on the influential 1995 comedy "Friday."
-
B.
Patricia Blanchet
Patricia Blanchet is the widow of renowned American broadcast journalist Ed Bradley, known for her connection to his legacy in television news.
-
C.
Peggy Bellecourt
Peggy Bellecourt is known as the wife of Native American civil rights leader and American Indian Movement co-founder Clyde Bellecourt.
-
D.
Juanita Saint-Peyron
Juanita Saint-Peyron is best known as the wife of acclaimed French actor Michel Serrault.
-
E.
Jacqueline Belhomme
Jacqueline Belhomme is a French politician who serves as the mayor of the Paris suburb of Malakoff.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fbbf0b08190ba1ea3657d6db005 |
completed | April 14, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd27ff5b7081908ab27d5851b274ea |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 9, 2026, 10:22 p.m.