Triple

T16221208
Position Surface form Disambiguated ID Type / Status
Subject Statius Müller E393727 entity
Predicate placeOfDeath P21 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: [Statius Müller, placeOfDeath, Erlangen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erlangen
Context triple: [Statius Müller, placeOfDeath, 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 suburb in Melbourne, Australia, known for its diverse community, historic architecture, and access to the city via major tram routes.
  • 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_69d87f204df88190a8f88923decf9835 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e227fbd88081909fac3f075d5ea7f4 completed April 17, 2026, 12:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00354a20d081908288fb8c0e8b83b6 completed May 10, 2026, 7:35 a.m.
Created at: April 10, 2026, 5:03 a.m.