Triple

T1653184
Position Surface form Disambiguated ID Type / Status
Subject Mühlhausen, Prussia E35738 entity
Predicate formerNameOf P65 FINISHED
Object Mühlhausen, Saxony-Anhalt E35738 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: Mühlhausen, Saxony-Anhalt | Statement: [Mühlhausen, Prussia, formerNameOf, Mühlhausen, Saxony-Anhalt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mühlhausen, Saxony-Anhalt
Context triple: [Mühlhausen, Prussia, formerNameOf, Mühlhausen, Saxony-Anhalt]
  • A. Mühlhausen, Prussia chosen
    Mühlhausen, Prussia was a town in the former Kingdom of Prussia, notable as the birthplace of civil engineer and bridge designer John A. Roebling.
  • B. Eisenach
    Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
  • C. Wernigerode
    Wernigerode is a picturesque German town in Saxony-Anhalt known for its colorful half-timbered houses, medieval castle, and location on the northern slopes of the Harz Mountains.
  • D. Wittenau
    Wittenau is a locality in the Reinickendorf borough of Berlin, Germany, known primarily as a residential area with good transport connections.
  • E. Merseburg, East Germany
    Merseburg, East Germany was a town in the former German Democratic Republic known as an industrial and chemical industry center near Leipzig.
  • 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_69a8860568888190a32cd9f70acbba42 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a8a080c8190b6913d6830d74526 completed March 5, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad681db3408190a3b469e319486419 completed March 8, 2026, 12:14 p.m.
Created at: March 4, 2026, 7:29 p.m.