Triple

T5630994
Position Surface form Disambiguated ID Type / Status
Subject Tottenham, London, England E147829 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: [Tottenham, London, England, historicalCounty, Middlesex]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Middlesex
Context triple: [Tottenham, London, England, historicalCounty, Middlesex]
  • A. Middlesex
    Middlesex is a small town located in Yates County in the Finger Lakes region of New York State.
  • B. County of Middlesex
    The County of Middlesex is a historic county in southeast England that once encompassed much of what is now Greater London and surrounding areas.
  • C. Middlesex, England chosen
    Middlesex, England is a historic county in southeast England that once encompassed much of what is now Greater London.
  • D. Middlesex Parish
    Middlesex Parish was the former ecclesiastical parish name for the area that later became the town of Darien, Connecticut.
  • 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_69c00907bc8881909ed760d3ed73ef35 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0225cdcdc819095034f12c39ef755 completed March 22, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d2aab348190944cca5375e0ddb9 completed March 22, 2026, 8:12 p.m.
Created at: March 22, 2026, 3:40 p.m.