Triple

T90167
Position Surface form Disambiguated ID Type / Status
Subject Gloucester E1811 entity
Predicate borderedBy P224 FINISHED
Object Essex E30848 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: Essex | Statement: [Gloucester, borderedBy, Essex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Essex
Context triple: [Gloucester, borderedBy, Essex]
  • A. Essex chosen
    Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
  • B. Hampshire
    Hampshire is a county on England’s south coast known for its historic cities, naval and military heritage, and mix of rural countryside and coastal areas.
  • C. Essex County
    Essex County is a historic coastal county in northeastern Massachusetts that includes cities such as Lynn, Salem, and Lawrence.
  • D. 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.
  • E. Cheshire
    Cheshire is a ceremonial and historic county in North West England known for its rural landscapes, affluent towns, and production of Cheshire cheese.
  • 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_69a24d1a97dc819094e6c021fe9b05a7 completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a383e3575c8190932dcdc25503d06e completed March 1, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a38b8959dc8190b6ec8ef2583505a1 completed March 1, 2026, 12:42 a.m.
Created at: Feb. 28, 2026, 2:07 a.m.