Triple

T12621932
Position Surface form Disambiguated ID Type / Status
Subject Kovno E301401 entity
Predicate hasAlternativeName P39 FINISHED
Object Kowno E301401 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: Kowno | Statement: [Kovno, hasAlternativeName, Kowno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kowno
Context triple: [Kovno, hasAlternativeName, Kowno]
  • A. Wilno
    Wilno is a small rural community in eastern Ontario, Canada, known as the country's oldest Polish-Kashubian settlement.
  • B. Wilno
    Wilno is the historical Polish name for Vilnius, a major cultural and political center of the region that served as an important city in the interwar Second Polish Republic.
  • C. Kovno chosen
    Kovno is the historical name for Kaunas, a major city in Lithuania that was once part of the Russian Empire and had a significant Jewish community.
  • D. Alytus
    Alytus is a city in southern Lithuania known as a regional cultural and economic center on the banks of the Nemunas River.
  • E. Marijampolė
    Marijampolė is a city in southern Lithuania that serves as an important regional center for administration, culture, and industry.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d960c8671881909a102d28b0e7f603 completed April 10, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b86935c8190835f6a407be52ae3 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:14 p.m.