Triple
T14549448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sauverny |
E341374
|
entity |
| Predicate | hasBorderWith |
P224
|
FINISHED |
| Object | Versoix |
E29605
|
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: Versoix | Statement: [Sauverny, hasBorderWith, Versoix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Versoix Context triple: [Sauverny, hasBorderWith, Versoix]
-
A.
Versoix
chosen
Versoix is a Swiss municipality on the shores of Lake Geneva, known as a residential suburb of Geneva with lakeside promenades and a mix of urban and natural landscapes.
-
B.
VOXI
VOXI is a UK-based mobile virtual network operator brand offering flexible, contract-free mobile plans primarily aimed at younger customers and powered by Vodafone’s network.
-
C.
Festivoix
Festivoix is an annual music and arts festival held in Trois-Rivières, Quebec, featuring a diverse lineup of performances across multiple stages.
-
D.
Amazon Polly
Amazon Polly is a cloud-based text-to-speech service from Amazon Web Services that converts written text into natural-sounding speech using advanced deep learning.
-
E.
Vocia
Vocia is Biamp Systems’ networked paging and voice evacuation platform designed for scalable, distributed audio communication in commercial and public 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2ed2b4c8190945bd26531c71f1f |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a6344b08190a3c1124c6dd7da96 |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:23 a.m.