Triple

T19523374
Position Surface form Disambiguated ID Type / Status
Subject Pasažieru vilciens E488458 entity
Predicate hasServiceArea P82 FINISHED
Object Riga metropolitan area E116320 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: Riga metropolitan area | Statement: [Pasažieru vilciens, hasServiceArea, Riga metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riga metropolitan area
Context triple: [Pasažieru vilciens, hasServiceArea, Riga metropolitan area]
  • A. Riga Planning Region chosen
    Riga Planning Region is an administrative planning area in Latvia that encompasses the capital city of Riga and its surrounding municipalities for regional development and coordination.
  • B. 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.
  • C. Riga
    Riga is a town in the Sitamarhi district of the Indian state of Bihar.
  • D. Liepāja, Latvia
    Liepāja is a major port city on Latvia’s Baltic Sea coast, known for its historic architecture, naval heritage, and cultural life.
  • E. Daugavpils
    Daugavpils is Latvia’s second-largest city, known as the birthplace of abstract expressionist painter Mark Rothko and for its multicultural heritage and 19th-century fortress.
  • 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_69d8e8da8bec819081f400199491ccc3 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e636392444819094f6a2aa1cdf3d42 completed April 20, 2026, 2:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07ea2b0e8081909805e12711def1e3 completed May 16, 2026, 3:53 a.m.
Created at: April 10, 2026, 1:41 p.m.