Triple

T6963446
Position Surface form Disambiguated ID Type / Status
Subject British Rail Class 700 E161427 entity
Predicate builtAt P283 FINISHED
Object Krefeld, Germany E398502 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: Krefeld, Germany | Statement: [British Rail Class 700, builtAt, Krefeld, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krefeld, Germany
Context triple: [British Rail Class 700, builtAt, Krefeld, Germany]
  • A. Krefeld, Germany
    Krefeld, Germany is an industrial city in North Rhine-Westphalia known historically for its textile and silk production.
  • B. Krefeld chosen
    Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
  • C. Weinheim, Germany
    Weinheim, Germany is a town in the state of Baden-Württemberg known for its historic old town, twin castles, and role as a regional economic and publishing center.
  • D. Lünen, Germany
    Lünen is a mid-sized industrial and residential city in North Rhine-Westphalia, western Germany, situated on the Lippe River and known for its historical coal-mining heritage.
  • E. Brühl, Germany
    Brühl, Germany is a town in North Rhine-Westphalia known for its UNESCO-listed Augustusburg and Falkenlust palaces and its proximity to Cologne.
  • 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_69c68853cff881908439d488924a8283 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6daf197b0819085bd0433c8a7f716 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c758a0e5bc819098206940fc3ac623 completed March 28, 2026, 4:27 a.m.
Created at: March 27, 2026, 2:30 p.m.