Triple

T1886132
Position Surface form Disambiguated ID Type / Status
Subject Ware, Hertfordshire E39968 entity
Predicate locatedIn P40 FINISHED
Object Hertfordshire E60268 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: Hertfordshire | Statement: [Ware, Hertfordshire, locatedIn, Hertfordshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hertfordshire
Context triple: [Ware, Hertfordshire, locatedIn, Hertfordshire]
  • A. Hertfordshire chosen
    Hertfordshire is a county in southern England known for its historic market towns, countryside, and proximity to London.
  • B. Bedfordshire
    Bedfordshire is a ceremonial and non-metropolitan county in the East of England, known for its mix of rural countryside, market towns, and the large town of Luton.
  • C. Buckinghamshire
    Buckinghamshire is a ceremonial and non-metropolitan county in South East England, known for its historic towns, Chiltern Hills countryside, and proximity to London.
  • D. Northamptonshire
    Northamptonshire is a historic, landlocked county in the East Midlands of England known for its market towns, rural landscapes, and long association with the footwear and leather industries.
  • E. Essex
    Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
  • 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_69a88633e4fc8190b7eb40463e048ec5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb12032c881909cd93e3601906f48 completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69b54c0e702081909384b804fb1ade90 completed March 14, 2026, 11:52 a.m.
Created at: March 4, 2026, 7:34 p.m.