Triple

T17019487
Position Surface form Disambiguated ID Type / Status
Subject Kėdainiai District Municipality E412907 entity
Predicate hasPart P35 FINISHED
Object town of 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: town of Kėdainiai | Statement: [Kėdainiai District Municipality, hasPart, town of Kėdainiai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: town of Kėdainiai
Context triple: [Kėdainiai District Municipality, hasPart, town of Kėdainiai]
  • A. Kėdainiai chosen
    Kėdainiai is a historic city in central Lithuania known for its well-preserved old town and multicultural heritage.
  • B. Terikiai
    Terikiai is a village settlement located on the atoll of Tabiteuea in the island nation of Kiribati.
  • C. Sakiai
    Sakiai is a small town in southwestern Lithuania known for its proximity to the Russian and Polish borders and its role as a local administrative and cultural center.
  • D. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • E. New Town of Kaunas
    The New Town of Kaunas is a central district of Kaunas, Lithuania, characterized by its 19th–20th century urban layout, commercial streets, and more modern architecture compared to the historic Old Town.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d481a0988190a13d0928e0c7ebbf completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b4d6cb881909b64b4368fd97fa9 completed May 10, 2026, 11:57 p.m.
Created at: April 10, 2026, 5:33 a.m.