Triple

T5807729
Position Surface form Disambiguated ID Type / Status
Subject Franconia E128786 entity
Predicate contains P35 FINISHED
Object Coburg E214909 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: Coburg | Statement: [Franconia, contains, Coburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coburg
Context triple: [Franconia, contains, Coburg]
  • A. Coburg chosen
    Coburg is a historic town in northern Bavaria, Germany, known for its well-preserved medieval architecture and its former role as the seat of the Duchy of Saxe-Coburg and Gotha.
  • B. Bamberg
    Bamberg is a historic city in northern Bavaria, Germany, renowned for its well-preserved medieval old town and status as a UNESCO World Heritage Site.
  • C. Kronach
    Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
  • D. Altenburg
    Altenburg is a historic town in eastern Thuringia, Germany, known for its playing-card tradition and as the birthplace of the card game Skat.
  • E. Schweinfurt
    Schweinfurt is a city in northern Bavaria, Germany, historically known for its ball bearing industry and as a strategic target during World War II.
  • 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_69c0084788848190bcf71f6bc5d71597 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02b17417081908779741b9bfbb720 completed March 22, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d66fdb1c81909ca125e5918b0997 completed March 29, 2026, 7:36 a.m.
Created at: March 22, 2026, 3:52 p.m.