Triple

T750263
Position Surface form Disambiguated ID Type / Status
Subject Ruffner Mountain Nature Preserve E15431 entity
Predicate city P40 FINISHED
Object 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: Birmingham | Statement: [Ruffner Mountain Nature Preserve, city, Birmingham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Birmingham
Context triple: [Ruffner Mountain Nature Preserve, city, 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. 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a6304e0c8190827fb57c5cac2da9 completed March 1, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf4b62b08190bc8d5978595ce60b completed March 4, 2026, 6:20 a.m.
Created at: March 1, 2026, 7:37 p.m.