Triple

T7931776
Position Surface form Disambiguated ID Type / Status
Subject Moonshot Factory E184204 entity
Predicate hasProject P14971 FINISHED
Object Waymo E300866 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: Waymo | Statement: [Moonshot Factory, hasProject, Waymo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waymo
Context triple: [Moonshot Factory, hasProject, Waymo]
  • A. Waymo chosen
    Waymo is an autonomous driving technology company, originally a Google self-driving car project, that develops and operates self-driving vehicles and robotaxi services.
  • B. General Motors (via Cruise)
    General Motors (via Cruise) is the U.S. automaker’s autonomous vehicle subsidiary focused on developing and deploying self-driving car technology.
  • C. Uber Advanced Technologies Group
    Uber Advanced Technologies Group was Uber’s self-driving car research and development division focused on autonomous vehicle technologies.
  • D. Mobileye
    Mobileye is an Israeli technology company specializing in advanced driver-assistance systems and autonomous driving solutions, known for its computer vision and mapping technologies used by major automakers worldwide.
  • E. Boston Dynamics
    Boston Dynamics is an American engineering and robotics company renowned for creating advanced, highly mobile robots such as Atlas, Spot, and Handle.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3ace87f081908635769942645e78 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c041e588190bfbf251ed88d5bcd completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:07 p.m.