Triple

T7750942
Position Surface form Disambiguated ID Type / Status
Subject Dara Khosrowshahi E175758 entity
Predicate employer P7 FINISHED
Object Uber Technologies, Inc. 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, Inc. | Statement: [Dara Khosrowshahi, employer, Uber Technologies, Inc.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uber Technologies, Inc.
Context triple: [Dara Khosrowshahi, employer, Uber Technologies, Inc.]
  • 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. Careem
    Careem is a Dubai-based ride-hailing and delivery company operating across the Middle East, North Africa, and South Asia, acquired by Uber to expand its presence in the region.
  • 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_69c69960b3588190a53aa590d31d9544 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703b264c0819095c37534a676531d completed March 27, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be576274819092e5ebdbcf2361da completed March 29, 2026, 5:53 a.m.
Created at: March 27, 2026, 4:08 p.m.