Triple

T20061994
Position Surface form Disambiguated ID Type / Status
Subject Verkehrs- und Tarifverbund Stuttgart E499497 entity
Predicate hasMobileApp P1395 FINISHED
Object VVS app NE NERFINISHED

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: VVS app | Statement: [Verkehrs- und Tarifverbund Stuttgart, hasMobileApp, VVS app]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VVS app
Context triple: [Verkehrs- und Tarifverbund Stuttgart, hasMobileApp, VVS app]
  • A. VVS chosen
    VVS is the public transport association and integrated fare network serving Stuttgart and its surrounding region in Germany.
  • B. VVS
    VVS was the air force branch of the Soviet Union’s armed forces, responsible for military aviation and air defense operations.
  • C. integrated with VVS
    Integrated with VVS is the unified public transport fare system covering Stuttgart and its surrounding region, allowing seamless travel across various transit modes and operators.
  • D. VVSS
    VVSS (Vertical Volute Spring Suspension) is an early U.S. tank suspension system using vertical volute springs to support and cushion tracked armored vehicles.
  • E. Vy mobile app
    Vy mobile app is a mobile application that allows users to plan journeys and purchase tickets for Vy’s regional train services in Norway.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66376f2d4819081b9e1b265650e5b completed April 20, 2026, 5:33 p.m.
Created at: April 11, 2026, 3:39 p.m.