Triple

T1032760
Position Surface form Disambiguated ID Type / Status
Subject Prince Bernhard of the Netherlands E22288 entity
Predicate placeOfBirth P1 FINISHED
Object Jena E60682 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: Jena | Statement: [Prince Bernhard of the Netherlands, placeOfBirth, Jena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jena
Context triple: [Prince Bernhard of the Netherlands, placeOfBirth, Jena]
  • A. Jena chosen
    Jena is a historic university city in the German state of Thuringia, known for its role in optics, philosophy, and science.
  • B. Neustrelitz
    Neustrelitz is a town in northeastern Germany known for hosting a key research center of the German Aerospace Center (DLR), particularly focused on satellite data and space-related technologies.
  • C. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • D. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • E. 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.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b811916481908c05c2dd5ec802ec completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae95c9bbfc81909a02cdca9c859d01 completed March 9, 2026, 9:41 a.m.
Created at: March 1, 2026, 7:41 p.m.