Triple

T13625102
Position Surface form Disambiguated ID Type / Status
Subject Aurora Innovation E325557 entity
Predicate partner P1136 FINISHED
Object Uber Freight 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 Freight | Statement: [Aurora Innovation, partner, Uber Freight]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uber Freight
Context triple: [Aurora Innovation, partner, Uber Freight]
  • A. GrabExpress
    GrabExpress is Grab’s on-demand parcel and document delivery service operating across various Southeast Asian cities.
  • B. Trucking Unlimited
    Trucking Unlimited was a trucking industry organization involved in a notable U.S. Supreme Court antitrust case concerning the use of governmental and judicial processes to restrict competitors.
  • C. 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.
  • D. Shipt
    Shipt is a same-day delivery and personal shopping service that partners with retailers to deliver groceries and household essentials to customers.
  • E. Swift Transportation
    Swift Transportation is one of the largest truckload motor carriers in the United States, providing nationwide freight transportation and logistics services.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbbe9c72c88190be3d7a3f2e96afbc completed April 12, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77fa4c5fc8190bd791f181fce2aa1 completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:50 p.m.