Triple

T682289
Position Surface form Disambiguated ID Type / Status
Subject Brentford E13207 entity
Predicate historicalCounty P1069 FINISHED
Object Middlesex E14852 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: Middlesex | Statement: [Brentford, historicalCounty, Middlesex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Middlesex
Context triple: [Brentford, historicalCounty, Middlesex]
  • A. Middlesex, England chosen
    Middlesex, England is a historic county in southeast England that once encompassed much of what is now Greater London.
  • B. Essex
    Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
  • C. Middlesex County
    Middlesex County is a populous county in central New Jersey known for its diverse suburban communities, major transportation hubs, and proximity to New York City.
  • D. Suffolk
    Suffolk is a historic rural county in eastern England known for its coastal towns, medieval villages, and agricultural landscapes.
  • E. Berkshire
    Berkshire is a historic county in South East England known for its royal connections, including Windsor Castle, and its mix of affluent towns and rural landscapes.
  • 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_69a4933e0f98819097d22766c49b61b8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a06f9ee88190a2d757aacd8e3f5b completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d6cdc9c81909eb3240c00fa530d completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:36 p.m.