Triple

T2497409
Position Surface form Disambiguated ID Type / Status
Subject Zułów E52183 entity
Predicate locatedIn P40 FINISHED
Object Vilnius County E103823 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: Vilnius County | Statement: [Zułów, locatedIn, Vilnius County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vilnius County
Context triple: [Zułów, locatedIn, Vilnius County]
  • A. Kaunas County
    Kaunas County is an administrative region in central Lithuania that encompasses the country’s second-largest city, Kaunas, and serves as an important economic and cultural hub.
  • B. Vilnius Region chosen
    Vilnius Region is a historical area in and around the city of Vilnius, contested by Poland and Lithuania in the 20th century and later incorporated into the Lithuanian SSR under Soviet rule.
  • C. Alytus
    Alytus is a city in southern Lithuania known as a regional cultural and economic center on the banks of the Nemunas River.
  • D. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • E. Samogitia
    Samogitia is a historic ethnographic region in northwestern Lithuania known for its distinct Samogitian dialect, strong cultural identity, and late Christianization compared to the rest of Europe.
  • 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_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1ad2f8c81908853e97d75081e84 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b8789c88190b0300af1260eb9bd completed March 9, 2026, 8:20 p.m.
Created at: March 6, 2026, 9:46 p.m.