Triple
T20748731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Marie Vilain |
E510659
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Viry-Châtillon |
—
|
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: Viry-Châtillon | Statement: [Jean-Marie Vilain, workLocation, Viry-Châtillon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viry-Châtillon Context triple: [Jean-Marie Vilain, workLocation, Viry-Châtillon]
-
A.
Viry-Châtillon
chosen
Viry-Châtillon is a suburban commune in the southern outskirts of Paris, France, known for its residential character and location along the Seine River in the Essonne department.
-
B.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
C.
Villeré
Villeré is a French surname associated with individuals such as Marie Laure Villeré.
-
D.
Chauvigny
Chauvigny is a historic town in western France known for its medieval fortifications and picturesque setting in the Vienne department of the Nouvelle-Aquitaine region.
-
E.
Vaujours
Vaujours is a small suburban commune in the northeastern outskirts of Paris, France.
- 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_69e0b4c845e88190b4c5f3ae79291182 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c228af288190a20829d45c034c24 |
completed | April 21, 2026, 12:17 a.m. |
Created at: April 16, 2026, 12:34 p.m.