Triple

T17019486
Position Surface form Disambiguated ID Type / Status
Subject Kėdainiai District Municipality E412907 entity
Predicate administrativeCenter P1474 FINISHED
Object Kėdainiai 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: Kėdainiai | Statement: [Kėdainiai District Municipality, administrativeCenter, Kėdainiai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kėdainiai
Context triple: [Kėdainiai District Municipality, administrativeCenter, Kėdainiai]
  • A. Kėdainiai chosen
    Kėdainiai is a historic city in central Lithuania known for its well-preserved old town and multicultural heritage.
  • B. Kuršėnai
    Kuršėnai is a town in northern Lithuania known for its pottery traditions and location along the Venta River.
  • C. Kelmė
    Kelmė is a small town in northern Lithuania known as the administrative center of Kelmė District Municipality and for its historic manor and surrounding rural landscapes.
  • D. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • E. Terikiai
    Terikiai is a village settlement located on the atoll of Tabiteuea in the island nation of Kiribati.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d481a0988190a13d0928e0c7ebbf completed April 18, 2026, 6:59 p.m.
Created at: April 10, 2026, 5:33 a.m.