Triple
T4390917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | François Chollet |
E99359
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Chollet |
E99359
|
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: Chollet | Statement: [François Chollet, familyName, Chollet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chollet Context triple: [François Chollet, familyName, Chollet]
-
A.
Rocard
Rocard is a French surname most notably associated with Michel Rocard, a former Prime Minister of France and prominent Socialist politician.
-
B.
Choully
Choully is a small wine-producing village in the commune of Satigny in the canton of Geneva, Switzerland.
-
C.
Aspremont
Aspremont is a small picturesque commune in southeastern France, situated in the hills above Nice in the Alpes-Maritimes department.
-
D.
Mauroy
Mauroy is a French surname most notably associated with Pierre Mauroy, a former Prime Minister of France and prominent Socialist politician.
-
E.
François Chollet
chosen
François Chollet is a French software engineer and AI researcher best known as the creator of the Keras deep learning library and a prominent advocate for practical, human-centric machine learning.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352843d7c8190929b94c94eaa63df |
completed | March 12, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e530428881908d125971263bd747 |
completed | March 14, 2026, 10:46 p.m. |
Created at: March 12, 2026, 11:19 p.m.