Triple

T8200662
Position Surface form Disambiguated ID Type / Status
Subject KR E191562 entity
Predicate represents P129 FINISHED
Object city of Krefeld 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: city of Krefeld | Statement: [KR, represents, city of Krefeld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Krefeld
Context triple: [KR, represents, city of Krefeld]
  • 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. City of Essen
    The City of Essen is a major urban center in Germany’s Ruhr area, historically significant as a medieval ecclesiastical seat and later as an important industrial and coal-mining hub.
  • D. Mülheim an der Ruhr
    Mülheim an der Ruhr is a city in western Germany’s Ruhr area, known for its industrial heritage, riverside setting on the Ruhr River, and role as a regional economic and cultural center.
  • E. Recklinghausen
    Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
  • 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_69ca82c6e9548190a4c5ca14516e4417 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb5df565dc819099537fc06b694b40 completed March 31, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf5120159881908361bf9cb81e3932 completed April 3, 2026, 5:33 a.m.
Created at: March 30, 2026, 5:43 p.m.