Triple

T2606741
Position Surface form Disambiguated ID Type / Status
Subject Eisleben E58677 entity
Predicate hasAlternativeName P39 FINISHED
Object Lutherstadt Eisleben E58677 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: Lutherstadt Eisleben | Statement: [Eisleben, hasAlternativeName, Lutherstadt Eisleben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lutherstadt Eisleben
Context triple: [Eisleben, hasAlternativeName, Lutherstadt Eisleben]
  • A. Eisleben chosen
    Eisleben is a historic town in the German state of Saxony-Anhalt, best known as the birthplace of Protestant Reformer Martin Luther.
  • 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. Wittenberg
    Wittenberg is a historic German city best known as the cradle of the Protestant Reformation and the place where Martin Luther taught and preached.
  • D. Naumburg
    Naumburg is a historic town in the German state of Saxony-Anhalt, known for its medieval cathedral and as the childhood home of philosopher Friedrich Nietzsche.
  • E. Merseburg
    Merseburg is a historic town in the German state of Saxony-Anhalt, known for its medieval cathedral and role as an important cultural and administrative center on the River Saale.
  • 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_69ab4ac3523881909679750c9f8c2dec completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd865c9908190be7e1b572a43972f completed March 7, 2026, 7:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69af907ebc348190b1556a2104cba6f1 completed March 10, 2026, 3:31 a.m.
Created at: March 6, 2026, 9:49 p.m.