Triple
T19741576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chamalières |
E474134
|
entity |
| Predicate | officialName |
P66
|
FINISHED |
| Object | Chamalières |
E474134
|
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: Chamalières | Statement: [Chamalières, officialName, Chamalières]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chamalières Context triple: [Chamalières, officialName, Chamalières]
-
A.
Chamalières
chosen
Chamalières is a commune in central France, near Clermont-Ferrand, known historically as a spa town and for its residential character.
-
B.
Chamblon
Chamblon is a small municipality in the canton of Vaud in western Switzerland.
-
C.
Bourgueil
Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
-
D.
Villeneuve-d'Allier
Villeneuve-d'Allier is a small French commune in the Haute-Loire department of south-central France, situated along the Allier River.
-
E.
Chevilly-Larue
Chevilly-Larue is a suburban commune in the southern outskirts of Paris, France, known for its residential character and proximity to major transport routes and facilities.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65162382081909bd5a251d7da7f75 |
completed | April 20, 2026, 4:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09c289750081908188a60ea7a0062f |
completed | May 17, 2026, 1:28 p.m. |
Created at: April 10, 2026, 1:47 p.m.