Triple
T18921359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Pierre Sauvage |
E462865
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jean-Pierre |
—
|
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: Jean-Pierre | Statement: [Jean-Pierre Sauvage, givenName, Jean-Pierre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean-Pierre Context triple: [Jean-Pierre Sauvage, givenName, Jean-Pierre]
-
A.
Jean-Pierre
chosen
Jean-Pierre is a French given name commonly used as a masculine compound first name.
-
B.
Jean-Pierre Bel
Jean-Pierre Bel is a French politician best known for serving as President of the French Senate from 2011 to 2014.
-
C.
Jean-Claude Petit
Jean-Claude Petit is a French composer and arranger best known for his film scores and collaborations with prominent European directors.
-
D.
Jean-Yves
Jean-Yves is a French masculine given name, typically used as a compound first name combining "Jean" and "Yves."
-
E.
Jean-Pierre Olivier
Jean-Pierre Olivier is a scholar and epigrapher known for his research on Aegean scripts, particularly the undeciphered Cretan hieroglyphs.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c9b3b93c819085032d8251a43ca8 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 10, 2026, 11:59 a.m.