Triple

T22829159
Position Surface form Disambiguated ID Type / Status
Subject Landkreis Karlsruhe E565748 entity
Predicate contains P35 FINISHED
Object Bretten 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: Bretten | Statement: [Landkreis Karlsruhe, contains, Bretten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bretten
Context triple: [Landkreis Karlsruhe, contains, Bretten]
  • A. Bretten chosen
    Bretten is a historic town in the German state of Baden-Württemberg, known as the birthplace of the Protestant reformer Philip Melanchthon.
  • B. Blaubeuren
    Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
  • C. Rastatt
    Rastatt is a historic town in southwestern Germany, known for its Baroque architecture and its role as the site of significant early 18th-century peace negotiations.
  • D. Rottweil
    Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
  • E. Tuttlingen
    Tuttlingen is a town in the state of Baden-Württemberg in southern Germany, known as a major center of the medical technology and surgical instrument industry.
  • 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_69e24585ab1c81909b2b5065d15805d5 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17e2a0e308190941064965346f890 completed April 29, 2026, 3:42 a.m.
Created at: April 17, 2026, 3:34 p.m.