Triple

T11724504
Position Surface form Disambiguated ID Type / Status
Subject Tournon-sur-Rhône E278725 entity
Predicate twinnedWith P1072 FINISHED
Object Kronach E375518 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: Kronach | Statement: [Tournon-sur-Rhône, twinnedWith, Kronach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kronach
Context triple: [Tournon-sur-Rhône, twinnedWith, Kronach]
  • A. Kronach chosen
    Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
  • B. Kulmbach
    Kulmbach is a historic Bavarian town in northern Germany renowned for its beer brewing tradition and its hilltop Plassenburg Castle.
  • C. Schleiz
    Schleiz is a historic town in eastern Thuringia, Germany, known for its role as a former princely residence and for the nearby Schleizer Dreieck motor racing circuit.
  • D. Markranstädt
    Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
  • E. Döbeln
    Döbeln is a small town in the German state of Saxony, known for its historic center and location between the cities of Leipzig, Dresden, and Chemnitz.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4d603cc8190b2e68d0bdd793362 completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbaa8acc8190839b9a9f9f821168 completed May 3, 2026, 4:14 a.m.
Created at: April 8, 2026, 9:41 p.m.