Triple

T4855913
Position Surface form Disambiguated ID Type / Status
Subject Tampere E108535 entity
Predicate hasTwinTown P919 FINISHED
Object Tartu E43129 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: Tartu | Statement: [Tampere, hasTwinTown, Tartu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tartu
Context triple: [Tampere, hasTwinTown, Tartu]
  • A. Tartu chosen
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • B. Tallinn
    Tallinn is the capital and largest city of Estonia, a historic Baltic Sea port known for its well-preserved medieval Old Town and strategic maritime location.
  • C. Pärnu
    Pärnu is a coastal city in southwestern Estonia known as a popular summer resort and spa destination on the Baltic Sea.
  • D. Viljandi
    Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
  • E. Reval
    Reval is the historical German name for Tallinn, the capital city and major port of present-day Estonia on the Baltic Sea.
  • 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_69bd440a89548190a5f14ba6da6b97dc completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d3df75c8190830e2c927cc5a4f8 completed March 20, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67dd3df4819092a59dfb85d10683 completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:26 p.m.