Triple

T691808
Position Surface form Disambiguated ID Type / Status
Subject Regions Field E13808 entity
Predicate owner P347 FINISHED
Object City of Birmingham E56101 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: City of Birmingham | Statement: [Regions Field, owner, City of Birmingham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Birmingham
Context triple: [Regions Field, owner, City of Birmingham]
  • A. Birmingham
    Birmingham is a major industrial city in England’s West Midlands, historically significant for its manufacturing heritage and heavy bombing during the Second World War.
  • B. Birmingham chosen
    Birmingham is a major industrial and cultural city in the southern United States, known historically for its steel production and pivotal role in the Civil Rights Movement.
  • C. Wolverhampton
    Wolverhampton is a large industrial city in England’s West Midlands, known historically for its role in the coal, steel, and manufacturing industries.
  • D. Coventry
    Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
  • E. Sheffield
    Sheffield is a major industrial city in South Yorkshire, England, historically renowned for its steel production and role in the Industrial Revolution.
  • 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_69a493406c408190957eeec9048a8fb6 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a0aebde88190a49d421477713103 completed March 1, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d6ed1f881909fea81ce4308075b completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:36 p.m.