Triple

T2956200
Position Surface form Disambiguated ID Type / Status
Subject United States technology sector E79936 entity
Predicate majorCompany P597 FINISHED
Object Uber Technologies 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 Technologies | Statement: [United States technology sector, majorCompany, Uber Technologies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uber Technologies
Context triple: [United States technology sector, majorCompany, Uber Technologies]
  • A. Lyft
    Lyft is a major American ride-hailing and transportation company that connects passengers with drivers through a mobile app platform.
  • 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 Pro
    Uber Pro is a rewards and loyalty program that provides benefits and incentives to Uber drivers based on their performance and activity.
  • D. Didi Chuxing
    Didi Chuxing is a major Chinese ride-hailing and mobility technology company offering app-based transportation, taxi, and related services across numerous cities in China and abroad.
  • E. Postmates
    Postmates is an on-demand delivery service platform that connects users with local couriers to deliver food, groceries, and other goods from nearby merchants.
  • 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_69ad8b1276588190a374a0b12e0f7bdf completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad992998f08190ac9428310983172e completed March 8, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc8a10848190b8eec482252eb76b completed March 11, 2026, 5:24 a.m.
Created at: March 8, 2026, 2:57 p.m.