Triple

T8740483
Position Surface form Disambiguated ID Type / Status
Subject Port of Helsinki E207486 entity
Predicate connectsTo P845 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: [Port of Helsinki, connectsTo, Tallinn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tallinn
Context triple: [Port of Helsinki, connectsTo, 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 the capital and largest city of Latvia, a historic cultural and economic hub on the Baltic Sea known for its Art Nouveau architecture and significant port.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d4a0cf481909c770cb39fd00fcd completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf4287aa048190ba0263623d02b2ef completed April 3, 2026, 4:31 a.m.
Created at: March 30, 2026, 6:38 p.m.