Triple
T3911511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton of Saint-Genis-Pouilly |
E87330
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Chevry |
E410660
|
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: Chevry | Statement: [Canton of Saint-Genis-Pouilly, contains, Chevry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chevry Context triple: [Canton of Saint-Genis-Pouilly, contains, Chevry]
-
A.
Chevry
chosen
Chevry is a small French commune located in eastern France within the Ain department, near the Swiss border and the city of Geneva.
-
B.
Croisset
Croisset is a small riverside locality near Rouen in northern France, best known as the longtime residence and writing retreat of novelist Gustave Flaubert.
-
C.
Bourgueil
Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
-
D.
Vaucresson
Vaucresson is a suburban commune in the western outskirts of Paris, France, known for its residential character and green surroundings.
-
E.
Arnouville
Arnouville is a commune in the Val-d'Oise department in the northern suburbs of Paris, France.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed35e2d081908b5d87c7630e7ffc |
completed | March 9, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea458dd088190834a647c7316a83c |
completed | March 21, 2026, 1:59 p.m. |
Created at: March 9, 2026, 3:22 p.m.