Triple

T12968414
Position Surface form Disambiguated ID Type / Status
Subject Johannes Agricola E321328 entity
Predicate placeOfBirth P1 FINISHED
Object 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: Eisleben | Statement: [Johannes Agricola, placeOfBirth, Eisleben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eisleben
Context triple: [Johannes Agricola, placeOfBirth, 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. Wittenberge
    Wittenberge is a small town in the state of Brandenburg in northeastern Germany, situated on the Elbe River and known for its historic industrial architecture and riverside setting.
  • C. Village of Wittenberg
    The Village of Wittenberg is a small rural community in central Wisconsin known for its agricultural surroundings and local small-town character.
  • D. 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.
  • E. 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.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e407e5081909424fc0c22483c28 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8e6b31c8190b09276003f284f25 completed May 3, 2026, 2:54 a.m.
Created at: April 9, 2026, 8:32 p.m.