Triple
T3843648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | François-Cyrille Grange |
E93513
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | François-Cyrille |
E93513
|
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: François-Cyrille | Statement: [François-Cyrille Grange, givenName, François-Cyrille]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: François-Cyrille Context triple: [François-Cyrille Grange, givenName, François-Cyrille]
-
A.
François-Paul
François-Paul is the given name of François-Paul Brueys d’Aigalliers, a French naval officer and admiral who served during the French Revolutionary Wars.
-
B.
Philippe Denis
Philippe Denis is a cinematographer best known for his work on the animated film "Megamind."
-
C.
Phillippe
Phillippe is a given name and surname, typically a French-influenced variant of Philip, used for both real and fictional individuals.
-
D.
Nicolas Chapados
Nicolas Chapados is a Canadian entrepreneur and artificial intelligence researcher best known as a co-founder of the AI company Element AI.
-
E.
François-Cyrille Grange
chosen
François-Cyrille Grange is a French alpine skier best known for lighting the Olympic cauldron at the 1992 Winter Olympics in Albertville.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb4fd308190a636ba9dbbe57ed6 |
completed | March 9, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5040f93948190b104cf1b7db671b7 |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:18 p.m.