Triple

T10305393
Position Surface form Disambiguated ID Type / Status
Subject Ravensburg E241739 entity
Predicate hasNameInLanguage P15 FINISHED
Object Ravensburg (German) E241739 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: Ravensburg (German) | Statement: [Ravensburg, hasNameInLanguage, Ravensburg (German)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ravensburg (German)
Context triple: [Ravensburg, hasNameInLanguage, Ravensburg (German)]
  • A. Ravensburg chosen
    Ravensburg is a historic town in southern Germany’s Baden-Württemberg state, known for its well-preserved medieval old town and as the namesake of the Ravensburger game and puzzle company.
  • B. Rottweil
    Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
  • C. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • D. 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.
  • E. 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.
  • 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d309a4508190ad9de37171a64dba completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d58416081909a010e905d70e934 completed April 9, 2026, 3:30 a.m.
Created at: April 6, 2026, 11:46 a.m.