Triple

T702262
Position Surface form Disambiguated ID Type / Status
Subject Royal Warwickshire Regiment E14023 entity
Predicate associatedCity P3207 FINISHED
Object Birmingham E13669 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: Birmingham | Statement: [Royal Warwickshire Regiment, associatedCity, Birmingham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Birmingham
Context triple: [Royal Warwickshire Regiment, associatedCity, Birmingham]
  • A. Birmingham chosen
    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
    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. Manchester
    Manchester is a major city in northwest England known for its industrial heritage, vibrant cultural scene, and influential contributions to music, sport, and science.
  • D. Manchester
    Manchester is the most populous city in the U.S. state of New Hampshire and a major economic and cultural center for the region.
  • E. Wolverhampton
    Wolverhampton is a large industrial city in England’s West Midlands, known historically for its role in the coal, steel, and manufacturing industries.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a532dd708190ab91e515a07b441e completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b8341cf0819089d18c2c63192679 completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:36 p.m.