Triple

T19371202
Position Surface form Disambiguated ID Type / Status
Subject Ventspils International Airport E484539 entity
Predicate serves P98 FINISHED
Object Ventspils 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: Ventspils | Statement: [Ventspils International Airport, serves, Ventspils]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ventspils
Context triple: [Ventspils International Airport, serves, Ventspils]
  • A. Ventspils chosen
    Ventspils is a port city on Latvia’s Baltic Sea coast known for its major ice-free harbor, oil and cargo terminals, and well-preserved historic center.
  • B. Jelgava
    Jelgava is a city in central Latvia known for its historic Jelgava Palace and role as a regional cultural and educational center.
  • C. 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.
  • D. 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.
  • E. Paldiski
    Paldiski is a coastal town and former Soviet naval base in northwestern Estonia, located on the Pakri Peninsula by the Baltic Sea.
  • 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e619b09ef08190a8b420316c0b8eb3 completed April 20, 2026, 12:18 p.m.
Created at: April 10, 2026, 1:35 p.m.