Triple

T241648
Position Surface form Disambiguated ID Type / Status
Subject Uber E4943 entity
Predicate formerName P65 FINISHED
Object UberCab, 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: UberCab, Inc. | Statement: [Uber, formerName, UberCab, Inc.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UberCab, Inc.
Context triple: [Uber, formerName, UberCab, 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. Byfleet
    Byfleet is a village and former civil parish in southeast England, situated within the county of Surrey.
  • D. Cubic Transportation Systems
    Cubic Transportation Systems is a company specializing in automated fare collection and intelligent transportation solutions for public transit systems worldwide.
  • E. Keolis
    Keolis is a major French public transport operator that manages and operates bus, tram, metro, and rail networks in numerous cities worldwide.
  • 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_69a257c3d0708190b0871c4269d273e6 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25cee6f208190b996be4faa700910 completed Feb. 28, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a36cf2e84c81908d87847d498f96f4 completed Feb. 28, 2026, 10:32 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.