Triple

T2978155
Position Surface form Disambiguated ID Type / Status
Subject Silver Arrows E80446 entity
Predicate notableDriver P2087 FINISHED
Object Stirling Moss E150163 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: Stirling Moss | Statement: [Silver Arrows, notableDriver, Stirling Moss]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stirling Moss
Context triple: [Silver Arrows, notableDriver, Stirling Moss]
  • A. Sir Stirling Moss chosen
    Sir Stirling Moss was a legendary British racing driver, widely regarded as one of the greatest Formula One drivers never to win a World Championship.
  • B. Bruce McLaren
    Bruce McLaren was a New Zealand racing driver, engineer, and founder of the McLaren Formula One team, renowned for his contributions to motorsport both on and off the track.
  • C. Russell Carhouse
    Russell Carhouse is a major Toronto Transit Commission streetcar maintenance and storage facility located in Toronto, Canada.
  • D. Jim Clark
    Jim Clark is an American entrepreneur and computer scientist best known for co-founding Netscape and Silicon Graphics, playing a pivotal role in the early commercial development of the internet and computer graphics.
  • E. Jim Clark
    Jim Clark was a British film editor renowned for his work on numerous acclaimed movies across several decades, including major Hollywood and British productions.
  • 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_69ad8b15f6ac8190be5fd16a33edcb4f completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad999b0d50819093dac7678b887a9b completed March 8, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108ecef788190ad40dba81f1036c6 completed March 11, 2026, 6:17 a.m.
Created at: March 8, 2026, 2:58 p.m.