Triple

T19168876
Position Surface form Disambiguated ID Type / Status
Subject Mitau E469259 entity
Predicate locatedInPresentDay P40 FINISHED
Object Jelgava, Latvia 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: Jelgava, Latvia | Statement: [Mitau, locatedInPresentDay, Jelgava, Latvia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jelgava, Latvia
Context triple: [Mitau, locatedInPresentDay, Jelgava, Latvia]
  • A. Liepāja, Latvia
    Liepāja is a major port city on Latvia’s Baltic Sea coast, known for its historic architecture, naval heritage, and cultural life.
  • B. Jelgava chosen
    Jelgava is a city in central Latvia known for its historic Jelgava Palace and role as a regional cultural and educational center.
  • C. Ventspils
    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.
  • D. Kalsnava
    Kalsnava is a settlement in eastern Latvia known for its surrounding forests and inclusion within Madona Municipality.
  • E. Jūrmala
    Jūrmala is a popular Latvian resort city on the Gulf of Riga, known for its long sandy beaches, wooden architecture, and spa traditions.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f162ac648190a5f60c6a77b68304 completed April 20, 2026, 9:26 a.m.
Created at: April 10, 2026, 12:06 p.m.