Triple

T19528017
Position Surface form Disambiguated ID Type / Status
Subject Bielefeld viaduct E488581 entity
Predicate locatedNear P294 FINISHED
Object Brackwede NE NERFINISHED

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: Brackwede | Statement: [Bielefeld viaduct, locatedNear, Brackwede]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brackwede
Context triple: [Bielefeld viaduct, locatedNear, Brackwede]
  • A. Brackwede chosen
    Brackwede is a district of the city of Bielefeld in North Rhine-Westphalia, Germany, known historically as an independent town before its incorporation.
  • B. Farnhill
    Farnhill is a small village in North Yorkshire, England, situated on the hillside above the River Aire in the Aire Valley.
  • C. Bracebridge Heath
    Bracebridge Heath is a large village and civil parish in Lincolnshire, England, situated just south of the city of Lincoln.
  • D. Wickhambrook
    Wickhambrook is a rural village and civil parish in the county of Suffolk in eastern England.
  • E. Buckthorne
    Buckthorne is the fictional protagonist of the satirical work "Buckthorne and His Friends," around whom the story’s social observations and character interactions revolve.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8da8bec819081f400199491ccc3 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6363d43148190af25caaa57accf9b completed April 20, 2026, 2:20 p.m.
Created at: April 10, 2026, 1:41 p.m.