Triple

T616697
Position Surface form Disambiguated ID Type / Status
Subject Kensington E14419 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: [Kensington, historicalCounty, Middlesex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Middlesex
Context triple: [Kensington, 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. Suffolk
    Suffolk is a historic rural county in eastern England known for its coastal towns, medieval villages, and agricultural landscapes.
  • D. Windsor
    Windsor is a historic English town in Berkshire best known for Windsor Castle, one of the official residences of the British monarch and a major royal and military ceremonial site.
  • E. Windsor
    Windsor is the royal house and family name of the reigning British monarchs, adopted in the early 20th century and borne by Queen Elizabeth II and her descendants.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e22f3688190a512bec3f0347814 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a563c40fbc81908b117bc6139507d2 completed March 2, 2026, 10:17 a.m.
Created at: March 1, 2026, 7:35 p.m.