Triple

T22714075
Position Surface form Disambiguated ID Type / Status
Subject Leisi E561678 entity
Predicate hasCountryCapital P8146 FINISHED
Object Tallinn 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: Tallinn | Statement: [Leisi, hasCountryCapital, Tallinn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tallinn
Context triple: [Leisi, hasCountryCapital, 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 (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_69e2454f1348819088d83f420925a5c1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1790bdac88190976c83c9039c9d16 completed April 29, 2026, 3:20 a.m.
Created at: April 17, 2026, 3:18 p.m.