Triple

T6992996
Position Surface form Disambiguated ID Type / Status
Subject Friedrich Kohlrausch E162129 entity
Predicate birthPlace P1 FINISHED
Object Rinteln E427772 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: Rinteln | Statement: [Friedrich Kohlrausch, birthPlace, Rinteln]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rinteln
Context triple: [Friedrich Kohlrausch, birthPlace, Rinteln]
  • A. Rinteln chosen
    Rinteln is a historic town in Lower Saxony, Germany, situated on the River Weser and known for its well-preserved medieval architecture.
  • B. Rheinhausen
    Rheinhausen is a district of the German city of Duisburg, located on the western bank of the Rhine in North Rhine-Westphalia.
  • C. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • D. Ramstedt
    Ramstedt is a Finnish surname most notably borne by linguist and diplomat Gustaf John Ramstedt, known for his pioneering work in Altaic and Mongolic studies.
  • E. Neudorf
    Neudorf is a residential district of Strasbourg, France, known for its dense urban fabric, local commerce, and proximity to the city 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbc30fdc81909244d83c8178755c completed March 27, 2026, 7:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a161f088190bbc3c4e2815fa929 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:32 p.m.