Triple

T17242885
Position Surface form Disambiguated ID Type / Status
Subject Marijampolė County E418545 entity
Predicate hasSettlement P1068 FINISHED
Object Marijampolė NE NERFINISHED

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: Marijampolė | Statement: [Marijampolė County, hasSettlement, Marijampolė]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marijampolė
Context triple: [Marijampolė County, hasSettlement, Marijampolė]
  • A. Marijampolė chosen
    Marijampolė is a city in southern Lithuania that serves as an important regional center for administration, culture, and industry.
  • B. 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.
  • 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. Vilkaviškis
    Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
  • E. Radviliškis
    Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e21003c81908c884a3c8712676a completed April 19, 2026, 1:21 a.m.
Created at: April 10, 2026, 5:39 a.m.