Triple

T1762892
Position Surface form Disambiguated ID Type / Status
Subject Cariad E38696 entity
Predicate servesBrand P6337 FINISHED
Object Škoda E39971 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: Škoda | Statement: [Cariad, servesBrand, Škoda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Škoda
Context triple: [Cariad, servesBrand, Škoda]
  • A. Škoda chosen
    Škoda is a Czech automobile manufacturer known for producing practical, affordable cars and operating as a subsidiary brand within the Volkswagen Group.
  • B. BMW
    BMW is a German luxury automobile and motorcycle manufacturer renowned for its performance-oriented vehicles and engineering.
  • C. Opel
    Opel is a German automobile manufacturer known for producing a wide range of passenger cars and light commercial vehicles for the European market.
  • D. Audi
    Audi is a German luxury automobile manufacturer known for its premium vehicles, advanced engineering, and signature quattro all-wheel-drive technology.
  • E. Fiat
    Fiat is an Italian automobile manufacturer known for producing compact city cars and mass-market vehicles, now operating as a brand within the multinational automotive group Stellantis.
  • 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6465245c8190b1ee84628c62c529 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada98eb0348190a44e05393a2c6eff completed March 8, 2026, 4:53 p.m.
Created at: March 4, 2026, 7:31 p.m.