Triple

T4144313
Position Surface form Disambiguated ID Type / Status
Subject Central Lithuania E89346 entity
Predicate containsCity P294 FINISHED
Object Kėdainiai E412903 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: Kėdainiai | Statement: [Central Lithuania, containsCity, Kėdainiai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kėdainiai
Context triple: [Central Lithuania, containsCity, Kėdainiai]
  • A. Kėdainiai chosen
    Kėdainiai is a historic city in central Lithuania known for its well-preserved old town and multicultural heritage.
  • B. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • C. 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.
  • D. Trakai
    Trakai is a historic Lithuanian town famed for its medieval island castle and former status as a political center of the Grand Duchy of Lithuania.
  • E. Alytus
    Alytus is a city in southern Lithuania known as a regional cultural and economic center on the banks of the Nemunas River.
  • 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_69b5c6feae608190b677362d9c734165 completed March 14, 2026, 8:37 p.m.
Created at: March 9, 2026, 3:43 p.m.