Triple

T804607
Position Surface form Disambiguated ID Type / Status
Subject Boss E17400 entity
Predicate teamName P7598 FINISHED
Object Tartan Racing E95170 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: Tartan Racing | Statement: [Boss, teamName, Tartan Racing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tartan Racing
Context triple: [Boss, teamName, Tartan Racing]
  • A. Tartan Racing chosen
    Tartan Racing is an autonomous vehicle research team formed by Carnegie Mellon University and General Motors that gained prominence by winning the 2007 DARPA Urban Challenge.
  • B. Midland F1 Racing
    Midland F1 Racing was a short-lived Formula One team that competed in the mid-2000s under Russian ownership before being sold and rebranded.
  • C. RCS Sport
    RCS Sport is an Italian sports and media company best known for organizing major cycling races and other sporting events.
  • D. St Rollox Works
    St Rollox Works was a major railway engineering and locomotive repair facility in Glasgow, Scotland, historically significant for its role in maintaining and constructing rolling stock for British railways.
  • E. Gazoo Racing
    Gazoo Racing is Toyota’s global motorsport and high-performance division, responsible for its racing activities and sporty road car models.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aabebff08190880e4876ff58bcfe completed March 1, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d83cf448190a2205cd777386833 completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:38 p.m.