Triple

T10309569
Position Surface form Disambiguated ID Type / Status
Subject Uber Blue E241850 entity
Predicate communicationChannel P2798 FINISHED
Object Uber Driver app E233728 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: Uber Driver app | Statement: [Uber Blue, communicationChannel, Uber Driver app]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uber Driver app
Context triple: [Uber Blue, communicationChannel, Uber Driver app]
  • A. Uber Driver app chosen
    The Uber Driver app is a mobile application used by Uber’s driver-partners to receive trip requests, navigate, manage earnings, and access driver-related tools and information.
  • B. Uber driver-partners
    Uber driver-partners are independent drivers who use the Uber platform to provide ride-hailing and related transportation services to passengers.
  • C. Uber Pro
    Uber Pro is a rewards and loyalty program that provides benefits and incentives to Uber drivers based on their performance and activity.
  • D. Uber
    Uber is a global ride-hailing and technology company that connects passengers with drivers through a mobile app and has expanded into food delivery and freight services.
  • E. Free Now
    Free Now is a European mobility service provider and ride-hailing platform offering taxis, private hire vehicles, and other transport options via a mobile app.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d32a18ac81909b4efd8c1ba3e113 completed April 7, 2026, 9:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d7154b88190a0ae1dfa029b125e completed April 9, 2026, 3:30 a.m.
Created at: April 6, 2026, 11:47 a.m.