Triple

T1659854
Position Surface form Disambiguated ID Type / Status
Subject Home Counties E35879 entity
Predicate partlyIncludes P16474 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: [Home Counties, partlyIncludes, Hertfordshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hertfordshire
Context triple: [Home Counties, partlyIncludes, 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_69a88606aa808190aa0b421b4271f220 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61e142ac8190aa2fbd8f0826b5b2 completed March 6, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4880c8d4c819083a0f49598dbb2d2 completed March 13, 2026, 9:56 p.m.
Created at: March 4, 2026, 7:29 p.m.