Triple

T13214993
Position Surface form Disambiguated ID Type / Status
Subject Operation Barbarossa (Northern sector) E314586 entity
Predicate notableCityInTheater P104215 FINISHED
Object Tallinn E20558 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: Tallinn | Statement: [Operation Barbarossa (Northern sector), notableCityInTheater, Tallinn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tallinn
Context triple: [Operation Barbarossa (Northern sector), notableCityInTheater, Tallinn]
  • A. Tallinn chosen
    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.
  • B. Tartu
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • C. Helsinki
    Helsinki is the capital and largest city of Finland, known for its coastal location on the Baltic Sea, modern design, and vibrant cultural life.
  • D. Maardu
    Maardu is an industrial town in northern Estonia, located just east of the capital Tallinn in Harju County.
  • E. Riga
    Riga is a town in the Sitamarhi district of the Indian state of Bihar.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf28c9c819080d7b42d20f579d1 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a31c8748190a24256a7dd1e346b completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:18 p.m.