Triple

T5807726
Position Surface form Disambiguated ID Type / Status
Subject Franconia E128786 entity
Predicate contains P35 FINISHED
Object Erlangen E80092 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: Erlangen | Statement: [Franconia, contains, Erlangen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erlangen
Context triple: [Franconia, contains, Erlangen]
  • A. Erlangen chosen
    Erlangen is a city in northern Bavaria, Germany, known for its university, research institutions, and historical association with mathematician Emmy Noether.
  • B. Erlangen-Höchstadt
    Erlangen-Höchstadt is a rural district in the Bavarian region of Middle Franconia in Germany, known for encompassing towns such as Herzogenaurach and parts of the metropolitan area around Erlangen.
  • 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. Heilbronn
    Heilbronn is a city in the German state of Baden-Württemberg known for its industrial base, wine production, and role as a regional economic and educational hub.
  • E. Coburg
    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.
  • 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_69c0a17f77fc8190b2ad6f6c45d96e43 completed March 23, 2026, 2:12 a.m.
Created at: March 22, 2026, 3:52 p.m.