Triple

T10983610
Position Surface form Disambiguated ID Type / Status
Subject Gewehr 98 E259570 entity
Predicate usedBy P260 FINISHED
Object Lithuania E17692 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: Lithuania | Statement: [Gewehr 98, usedBy, Lithuania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lithuania
Context triple: [Gewehr 98, usedBy, Lithuania]
  • A. Lithuania chosen
    Lithuania is a Baltic nation in Northern Europe known for its medieval history, restored independence from the Soviet Union in 1990, and membership in both the European Union and NATO.
  • B. Latvia
    Latvia is a Baltic nation in Northern Europe known for its historic capital Riga, diverse cultural heritage, and membership in major international organizations such as the European Union and NATO.
  • C. Dzūkija
    Dzūkija is a historical ethnographic region in southeastern Lithuania known for its extensive forests, traditional rural culture, and distinctive dialect.
  • D. Latveria
    Latveria is a fictional Eastern European nation in Marvel Comics, best known as the technologically advanced yet oppressive kingdom ruled by the supervillain Doctor Doom.
  • E. Laietania
    Laietania was an ancient Iberian region along the northeastern coast of the Iberian Peninsula, roughly corresponding to part of modern Catalonia around present-day Barcelona.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d772ec55fc81909b2b15f2493dddc6 completed April 9, 2026, 9:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3743d16ac81909c2d4eb11713512b completed April 18, 2026, 12:08 p.m.
Created at: April 8, 2026, 9:24 p.m.