Triple

T8981659
Position Surface form Disambiguated ID Type / Status
Subject Julian Thomson E214543 entity
Predicate employer P7 FINISHED
Object Lotus Cars E187987 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: Lotus Cars | Statement: [Julian Thomson, employer, Lotus Cars]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lotus Cars
Context triple: [Julian Thomson, employer, Lotus Cars]
  • A. Lotus Cars chosen
    Lotus Cars is a British sports car manufacturer renowned for its lightweight, high-performance vehicles and engineering innovation.
  • B. Lotus
    The lotus is a sacred aquatic flower widely revered in Indian culture and religion, symbolizing purity, beauty, and spiritual enlightenment.
  • C. Lotus
    Lotus is a pioneering software company best known for its Lotus 1-2-3 spreadsheet program, which was a dominant application in the early days of personal computing.
  • D. Aston Martin
    Aston Martin is a British luxury sports car manufacturer renowned for its high-performance grand tourers and long association with the James Bond film franchise.
  • E. McLaren Automotive
    McLaren Automotive is a British high-performance sports car and supercar manufacturer renowned for its Formula 1–derived engineering and cutting-edge design.
  • 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_69ca839ea8b88190922c6a326ffcc0d3 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc67a76f748190a4abad5d53d58fa8 completed April 1, 2026, 12:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc974f0f8819085c63deb53b95b80 completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:03 p.m.