Triple

T7346786
Position Surface form Disambiguated ID Type / Status
Subject Gojek E169399 entity
Predicate hasService P182 FINISHED
Object GoRide E169396 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: GoRide | Statement: [Gojek, hasService, GoRide]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GoRide
Context triple: [Gojek, hasService, GoRide]
  • A. GrabCar
    GrabCar is a ride-hailing service under the Grab platform that connects passengers with private car drivers via a mobile app across Southeast Asia.
  • B. GrabBike chosen
    GrabBike is Grab’s on-demand motorcycle ride-hailing service that offers quick, affordable two-wheeled transportation in various Southeast Asian cities.
  • C. Uber Pool
    Uber Pool is a ride-sharing service from Uber that matches multiple passengers heading in similar directions to share a car and split the fare.
  • D. Ofo
    Ofo were a Native American people historically located in the Southeastern Woodlands, known for their Siouan language and eventual migration into present-day Mississippi and Louisiana.
  • E. Lyft
    Lyft is a major American ride-hailing and transportation company that connects passengers with drivers through a mobile app platform.
  • 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_69c68a5878888190968ce4d04db8d69f completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0f0329c8190a0182e3bf62604e5 completed March 27, 2026, 9:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa916ac881909acee8184b71dc85 completed March 28, 2026, 3:58 p.m.
Created at: March 27, 2026, 3:05 p.m.