Triple

T5943488
Position Surface form Disambiguated ID Type / Status
Subject Jelgava E132222 entity
Predicate hasRailConnectionTo P848 FINISHED
Object Liepāja E133373 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: Liepāja | Statement: [Jelgava, hasRailConnectionTo, Liepāja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liepāja
Context triple: [Jelgava, hasRailConnectionTo, Liepāja]
  • A. 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.
  • B. Riga
    Riga is a town in the Sitamarhi district of the Indian state of Bihar.
  • C. 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.
  • D. Liepāja, Latvia chosen
    Liepāja is a major port city on Latvia’s Baltic Sea coast, known for its historic architecture, naval heritage, and cultural life.
  • E. Valmiera
    Valmiera is a historic city in northern Latvia, situated on the Gauja River and known today as a regional economic and cultural center in the Vidzeme region.
  • 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0393641d0819081c6c44816d94e4e completed March 22, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3bd196081908361a38ca17309c6 completed March 23, 2026, 6:54 a.m.
Created at: March 22, 2026, 4:01 p.m.