Triple
T3700423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Jouvenet |
E78563
|
entity |
| Predicate | trainedBy |
P3665
|
FINISHED |
| Object | Laurent Jouvenet |
E397951
|
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: Laurent Jouvenet | Statement: [Jean Jouvenet, trainedBy, Laurent Jouvenet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laurent Jouvenet Context triple: [Jean Jouvenet, trainedBy, Laurent Jouvenet]
-
A.
Laurent Jouvenet
chosen
Laurent Jouvenet was a French painter of the 17th century, known as the father of the more famous Baroque artist Jean Jouvenet.
-
B.
Jean-Claude Olivier
Jean-Claude Olivier is a writer associated with the Juicy brand or publication.
-
C.
Jean-Philippe Lauer
Jean-Philippe Lauer was a French archaeologist best known for his decades-long work restoring and studying the Step Pyramid complex of Djoser at Saqqara in Egypt.
-
D.
Stéphane Préfontaine
Stéphane Préfontaine is a Canadian former middle-distance runner best known for serving as one of the final torchbearers who lit the Olympic cauldron at the 1976 Montreal Summer Olympics.
-
E.
Peter Biziou
Peter Biziou is a British cinematographer known for his work on films such as "Bugsy Malone" and the Oscar-winning "Mississippi Burning."
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc514eb6c8190b3b74a603c717729 |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b53367ad5c81909f7bcbbc967514b7 |
completed | March 14, 2026, 10:07 a.m. |
Created at: March 8, 2026, 3:26 p.m.