Triple
T19213661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Opron |
E480421
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Robert Opron |
—
|
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: Robert Opron | Statement: [Robert Opron, name, Robert Opron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Opron Context triple: [Robert Opron, name, Robert Opron]
-
A.
Robert Opron
chosen
Robert Opron was a renowned French automobile designer best known for his influential work at Citroën in the 1960s and 1970s, where he shaped several iconic models.
-
B.
J. André Fouilhoux
J. André Fouilhoux was a French-born American architect known for his influential modernist designs in the early 20th century, particularly in New York City.
-
C.
Frédéric Bricout
Frédéric Bricout is a French politician who serves as the mayor of the northern French city of Cambrai.
-
D.
Yves Jégo
Yves Jégo is a French politician known for his roles in the National Assembly and government, particularly on the center-right of the political spectrum.
-
E.
Jean-Noël Tassez
Jean-Noël Tassez was a French businessman and media executive best known for his central involvement in the Angolagate arms trafficking scandal.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa38c0e881908e9501ee21d0f266 |
completed | April 20, 2026, 10:04 a.m. |
Created at: April 10, 2026, 1:22 p.m.