Triple

T4040484
Position Surface form Disambiguated ID Type / Status
Subject Vauxhall E83933 entity
Predicate headquartersLocation P62 FINISHED
Object Luton E51115 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: Luton | Statement: [Vauxhall, headquartersLocation, Luton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luton
Context triple: [Vauxhall, headquartersLocation, Luton]
  • A. Luton chosen
    Luton is a large town in Bedfordshire, England, known for its international airport and diverse urban population.
  • B. Aylesbury
    Aylesbury is a historic market town in southern England that serves as an important commercial and administrative center in Buckinghamshire.
  • C. Hemel Hempstead
    Hemel Hempstead is a large town in southern England, known as a post-war New Town and major commercial and residential centre within Hertfordshire.
  • D. Hertford
    Hertford is a historic market town and the county town of Hertfordshire in southern England.
  • E. Milton Keynes
    Milton Keynes is a large, planned new town in Buckinghamshire, England, known for its grid road system, modern architecture, and extensive green spaces.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb39400881909d0f5430f04e441c completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56299dbe88190b36f4a488201acd8 completed March 14, 2026, 1:28 p.m.
Created at: March 9, 2026, 3:37 p.m.