Triple

T20105069
Position Surface form Disambiguated ID Type / Status
Subject Riga–Skulte railway E490145 entity
Predicate regionServed P82 FINISHED
Object Riga metropolitan area 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: Riga metropolitan area | Statement: [Riga–Skulte railway, regionServed, Riga metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riga metropolitan area
Context triple: [Riga–Skulte railway, regionServed, 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 a town in the Sitamarhi district of the Indian state of Bihar.
  • C. 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.
  • 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. Riga Municipality
    Riga Municipality is the local government area encompassing Latvia’s capital city, Riga, and its surrounding administrative territory.
  • 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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e666dbad30819082454f360f358131 completed April 20, 2026, 5:48 p.m.
Created at: April 11, 2026, 11:28 p.m.