Triple

T12678265
Position Surface form Disambiguated ID Type / Status
Subject Ostrołęka E302877 entity
Predicate hasRailConnectionTo P848 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: [Ostrołęka, hasRailConnectionTo, Białystok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Białystok
Context triple: [Ostrołęka, hasRailConnectionTo, 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961b1dff48190923290555ece5d89 completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed314bb9481908144c5399aa62ffa completed May 9, 2026, 6:24 a.m.
Created at: April 9, 2026, 5:20 p.m.