Triple

T21362082
Position Surface form Disambiguated ID Type / Status
Subject Tsukuba E526806 entity
Predicate hasSisterCity P919 FINISHED
Object Jena NE NERFINISHED

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: [Tsukuba, hasSisterCity, Jena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jena
Context triple: [Tsukuba, hasSisterCity, 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. Riedenburg
    Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51d8a308190b09113b3b3f9bc15 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b06b219c81908f7674ae459e7931 completed April 22, 2026, 11:26 a.m.
Created at: April 16, 2026, 5:08 p.m.