Triple
T14121803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germaine Franco |
E339923
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Germaine Franco |
E339923
|
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: Germaine Franco | Statement: [Germaine Franco, name, Germaine Franco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Germaine Franco Context triple: [Germaine Franco, name, Germaine Franco]
-
A.
Germaine Franco
chosen
Germaine Franco is an American film composer and songwriter known for her groundbreaking work on animated features, including composing the score for Disney’s "Encanto."
-
B.
Jacqueline Belhomme
Jacqueline Belhomme is a French politician who serves as the mayor of the Paris suburb of Malakoff.
-
C.
Lizette Hermant
Lizette Hermant was the wife of broadcasting pioneer and RCA leader David Sarnoff.
-
D.
Madeleine LeClerc
Madeleine LeClerc is a character in the film "Quills," depicted as a young laundress at the Charenton asylum who becomes entangled with the Marquis de Sade and his forbidden writings.
-
E.
Kim Germain
Kim Germain is a sports executive best known as the owner of the Frisco Fighters indoor football team.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de60942a588190beff0058a92f7051 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf07feb48190b7519204b4f789b4 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:22 p.m.