Triple

T2016901
Position Surface form Disambiguated ID Type / Status
Subject Garrett Camp E44014 entity
Predicate notableWork P4 FINISHED
Object Uber platform E4943 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 platform | Statement: [Garrett Camp, notableWork, Uber platform]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uber platform
Context triple: [Garrett Camp, notableWork, Uber platform]
  • A. Uber Pro
    Uber Pro is a rewards and loyalty program that provides benefits and incentives to Uber drivers based on their performance and activity.
  • B. Uber chosen
    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.
  • C. Uber Black
    Uber Black is Uber’s premium ride service offering high-end vehicles and professional drivers for a more luxurious travel experience.
  • D. Lyft
    Lyft is a major American ride-hailing and transportation company that connects passengers with drivers through a mobile app platform.
  • E. UberX
    UberX is Uber’s standard, budget-friendly ride option that connects riders with everyday drivers using their personal vehicles.
  • 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_69a8891201bc8190aca837be6de41579 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb8ccdb7c81909f6b3c96f79fcdfc completed March 7, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fe5ad548190b4a64c5320b99c6d completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:38 p.m.