Triple

T3785443
Position Surface form Disambiguated ID Type / Status
Subject North Hertfordshire district E85518 entity
Predicate hasBorderWith P224 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: [North Hertfordshire district, hasBorderWith, Luton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luton
Context triple: [North Hertfordshire district, hasBorderWith, 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_69aed937fa8881908208ef3801060826 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee3dd80f08190a1704521a764e22c completed March 9, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f04a35448190a57f431ef703b1e1 completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:13 p.m.