Triple

T3945733
Position Surface form Disambiguated ID Type / Status
Subject Kaunas Railway Station E92141 entity
Predicate connectsTo P845 FINISHED
Object Białystok E28010 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: Białystok | Statement: [Kaunas Railway Station, connectsTo, Białystok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Białystok
Context triple: [Kaunas Railway Station, connectsTo, Białystok]
  • A. Białystok chosen
    Białystok is a city in northeastern Poland best known as the birthplace of L. L. Zamenhof and the cradle of the international language Esperanto.
  • B. Bydgoszcz
    Bydgoszcz is a major city in northern Poland known as an important economic, cultural, and academic center on the Brda and Vistula rivers.
  • C. Olsztyn
    Olsztyn is a historic city in northern Poland known for its medieval architecture, lakes, and role as the capital of the Warmian-Masurian Voivodeship.
  • D. Lublin
    Lublin is a historic city in eastern Poland known as a major cultural, academic, and economic center and for its significant role in Polish political history.
  • E. Radom
    Radom is a city in central Poland known as an important regional industrial and cultural center.
  • 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_69aed965502c8190904ebad1203a4ae8 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef0d8841081908d2c1de8e5758017 completed March 9, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64b8e4dd88190be82d6e5ad9f2e7a completed March 27, 2026, 9:19 a.m.
Created at: March 9, 2026, 3:24 p.m.