Triple

T7423843
Position Surface form Disambiguated ID Type / Status
Subject Mies E171317 entity
Predicate hasNeighboringMunicipality 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: [Mies, hasNeighboringMunicipality, Versoix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Versoix
Context triple: [Mies, hasNeighboringMunicipality, 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. Vocia
    Vocia is Biamp Systems’ networked paging and voice evacuation platform designed for scalable, distributed audio communication in commercial and public facilities.
  • C. Whispersync for Voice
    Whispersync for Voice is an Amazon feature that lets users seamlessly switch between reading a Kindle ebook and listening to its Audible audiobook counterpart while keeping their place synchronized.
  • D. VOZ
    VOZ is the ICAO airline designator used to identify Virgin Australia in international aviation operations.
  • E. Tellme Networks
    Tellme Networks was a voice-recognition and interactive voice response (IVR) technology company best known for providing speech-enabled telephone services and platforms, later acquired by Microsoft.
  • 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_69c68a625d048190af70eb8b63bec5a0 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2eece588190905774e7151edcb8 completed March 27, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8fa20137081909a21ac366c19407f completed March 29, 2026, 10:08 a.m.
Created at: March 27, 2026, 3:12 p.m.