Triple

T4144328
Position Surface form Disambiguated ID Type / Status
Subject Central Lithuania E89346 entity
Predicate hasMajorCity P316 FINISHED
Object Jonava E414338 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: Jonava | Statement: [Central Lithuania, hasMajorCity, Jonava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonava
Context triple: [Central Lithuania, hasMajorCity, Jonava]
  • A. Jonava chosen
    Jonava is a Lithuanian industrial town and regional center situated along the Neris River in central Lithuania.
  • B. Vasai
    Vasai is a historic coastal town in western India, near Mumbai, known for its strategic importance under Portuguese and later British rule and as the site of the 1802 Treaty of Bassein.
  • C. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • D. Klaipėda
    Klaipėda is a Lithuanian port city on the Baltic Sea known as the country’s main maritime gateway and a key regional transport and industrial hub.
  • E. Elektrėnai
    Elektrėnai is a Lithuanian town best known for its major thermal power plant and artificial reservoir, which have made it an important energy and recreational center in the country.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af025d2984819095f299327cc399d5 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db72503c81909e9cf69f23d093fc completed March 14, 2026, 10:04 p.m.
Created at: March 9, 2026, 3:43 p.m.