Triple
T3303658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chavaniac-Lafayette |
E69394
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Le Puy-en-Velay |
E57445
|
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: Le Puy-en-Velay | Statement: [Chavaniac-Lafayette, hasNearbyCity, Le Puy-en-Velay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Puy-en-Velay Context triple: [Chavaniac-Lafayette, hasNearbyCity, Le Puy-en-Velay]
-
A.
Le Puy-en-Velay
chosen
Le Puy-en-Velay is a historic town in south-central France renowned for its volcanic landscape, Marian pilgrimage site, and traditional lace-making.
-
B.
Mont-Dore
Mont-Dore is a spa and ski resort town in central France’s Massif Central, known for its thermal springs and access to the nearby volcanic landscapes.
-
C.
Longjumeau
Longjumeau is a suburban commune in the southern outskirts of Paris, France, known for its residential character and proximity to major transport routes.
-
D.
Puy-de-Dôme
Puy-de-Dôme is a department in central France known for its volcanic landscapes, including the Chaîne des Puys and the iconic Puy de Dôme volcano.
-
E.
Échenevex
Échenevex is a small French commune in the Ain department of eastern France, near the Swiss border and the city of Geneva.
- 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0c662308190aad8b2a93e1c8a5c |
completed | March 8, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bb5d0b88190b1895fd352924862 |
completed | March 12, 2026, 11:26 p.m. |
Created at: March 8, 2026, 3:11 p.m.