Triple

T8460138
Position Surface form Disambiguated ID Type / Status
Subject Kovno, Russian Empire E200019 entity
Predicate nameInGerman P22792 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, Russian Empire, nameInGerman, Kowno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kowno
Context triple: [Kovno, Russian Empire, nameInGerman, 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_69ca83198c4c8190a337bf717d1813f5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe49fca788190a8728ff74f4d26f5 completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6cf9368081909cad61cdf6156a0e completed April 2, 2026, 1:19 p.m.
Created at: March 30, 2026, 6:10 p.m.