Triple

T4174659
Position Surface form Disambiguated ID Type / Status
Subject M1 motorway E86446 entity
Predicate passesNear P416 FINISHED
Object Derby 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 | Statement: [M1 motorway, passesNear, Derby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Derby
Context triple: [M1 motorway, passesNear, Derby]
  • A. Derby chosen
    Derby is a historic city in Derbyshire, England, known for its industrial heritage, particularly in railways and engineering.
  • B. Derby
    Derby is a small coastal town in Western Australia's Kimberley region, known as a gateway to the outback and for its large tidal variations and proximity to the Buccaneer Archipelago.
  • C. Derby
    Derby is a small historic city in Connecticut known for its location at the confluence of the Housatonic and Naugatuck Rivers and its industrial heritage.
  • D. Derby
    Derby is a neighborhood within the Brazilian city of Recife, known for its central location and urban character.
  • E. Derby City
    Derby City is a popular nickname for Louisville, Kentucky, reflecting the city's fame as home of the Kentucky Derby horse race.
  • 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02e9370481908eda048724261c2b completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f5428a0819082aaea8950a7c039 completed March 14, 2026, 3:31 p.m.
Created at: March 9, 2026, 3:45 p.m.