Triple

T2425685
Position Surface form Disambiguated ID Type / Status
Subject Derby E53520 entity
Predicate transportHubFor P423 FINISHED
Object Midlands E20314 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: Midlands | Statement: [Derby, transportHubFor, Midlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Midlands
Context triple: [Derby, transportHubFor, Midlands]
  • A. Midlands
    Midlands is a central province of Zimbabwe known for its mining activities and diverse mix of ethnic groups.
  • B. Midlands chosen
    The Midlands is a central region of England known for its mix of major industrial cities, historic towns, and rural landscapes, lying between the north and south of the country.
  • C. Midlands–North-West
    Midlands–North-West is a large European Parliament constituency in Ireland that covers much of the country’s western and northern regions, including towns such as Ballina in County Mayo.
  • D. North East
    North East is a rural town in northeastern Dutchess County, New York, known for its agricultural landscape and the village of Millerton.
  • E. Lowlands
    The Lowlands are a historically and culturally significant region of southern and eastern Scotland characterized by relatively flat, fertile terrain and dense population compared to the Highlands.
  • 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc99a773c819092d5f3c297b83887 completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf61088481909d79e822e4071456 completed March 9, 2026, 12:38 p.m.
Created at: March 6, 2026, 9:42 p.m.