Triple

T8574179
Position Surface form Disambiguated ID Type / Status
Subject Eastern Germany E203004 entity
Predicate contains P35 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: [Eastern Germany, contains, Jena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jena
Context triple: [Eastern Germany, contains, 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. Gotha
    Gotha is a historic German city in Thuringia known for its former ducal court, cultural heritage, and role as a residence of various German noble houses.
  • C. 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.
  • 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. Oschersleben
    Oschersleben is a town in the German state of Saxony-Anhalt, known for its motorsport race track Motorsport Arena Oschersleben.
  • 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_69ca8328ebe481909a8c038fa79959b4 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea947f188190af469babaa73ddf6 completed March 31, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f3391ff08190a725b0549fb0bc89 completed April 4, 2026, 11:17 a.m.
Created at: March 30, 2026, 6:21 p.m.