Triple

T2342789
Position Surface form Disambiguated ID Type / Status
Subject East Midlands Airport E45062 entity
Predicate servesMetropolitanArea P82 FINISHED
Object Derby urban area E53520 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: Derby urban area | Statement: [East Midlands Airport, servesMetropolitanArea, Derby urban area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Derby urban area
Context triple: [East Midlands Airport, servesMetropolitanArea, Derby urban area]
  • A. Derby City
    Derby City is a popular nickname for Louisville, Kentucky, reflecting the city's fame as home of the Kentucky Derby horse race.
  • B. Derby chosen
    Derby is a historic city in Derbyshire, England, known for its industrial heritage, particularly in railways and engineering.
  • C. Derby
    Derby is a neighborhood within the Brazilian city of Recife, known for its central location and urban character.
  • D. Sheffield City Region
    Sheffield City Region is an English metropolitan area and economic region centered on the city of Sheffield, encompassing surrounding towns and districts for coordinated governance and development.
  • E. Teesside urban area
    Teesside urban area is a large conurbation in North East England centered on Middlesbrough and surrounding towns, known for its industrial heritage and position along the River Tees.
  • 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_69a88917935081909b755dbf38e81024 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc6ae33e881909a81a0c0def59059 completed March 7, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea88113988190b89abfc01f5bf6f4 completed March 9, 2026, 11:01 a.m.
Created at: March 4, 2026, 7:52 p.m.