Triple

T9415357
Position Surface form Disambiguated ID Type / Status
Subject Białystok County E227003 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Czarna Białostocka
Czarna Białostocka is a small town in north-eastern Poland, situated in the Podlaskie Voivodeship and known for its surrounding forests and proximity to the regional capital Białystok.
E799314 NE FINISHED

How this triple was built (4 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: Czarna Białostocka | Statement: [Białystok County, hasUrbanCenter, Czarna Białostocka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czarna Białostocka
Context triple: [Białystok County, hasUrbanCenter, Czarna Białostocka]
  • A. Słupia
    Słupia is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
  • B. Biała
    Biała is a former town in southern Poland that historically developed as a separate urban center before being merged with Bielsko to form the modern city of Bielsko-Biała.
  • C. Krynica Morska
    Krynica Morska is a Polish seaside resort town on the Vistula Spit, known for its sandy beaches and tourism on the Baltic coast.
  • D. Ustka
    Ustka is a Baltic Sea coastal town in northern Poland known as a popular seaside resort and fishing port.
  • E. Trzebinia
    Trzebinia is a town in southern Poland known for its industrial character and location between Kraków and Katowice.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Czarna Białostocka
Triple: [Białystok County, hasUrbanCenter, Czarna Białostocka]
Generated description
Czarna Białostocka is a small town in north-eastern Poland, situated in the Podlaskie Voivodeship and known for its surrounding forests and proximity to the regional capital Białystok.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Czarna Białostocka
Target entity description: Czarna Białostocka is a small town in north-eastern Poland, situated in the Podlaskie Voivodeship and known for its surrounding forests and proximity to the regional capital Białystok.
  • A. Słupia
    Słupia is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
  • B. Biała
    Biała is a former town in southern Poland that historically developed as a separate urban center before being merged with Bielsko to form the modern city of Bielsko-Biała.
  • C. Krynica Morska
    Krynica Morska is a Polish seaside resort town on the Vistula Spit, known for its sandy beaches and tourism on the Baltic coast.
  • D. Ustka
    Ustka is a Baltic Sea coastal town in northern Poland known as a popular seaside resort and fishing port.
  • E. Trzebinia
    Trzebinia is a town in southern Poland known for its industrial character and location between Kraków and Katowice.
  • F. None of above. chosen

Provenance (5 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_69ca84359e7c819091148ba4b670e436 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd68c7bd648190b17f082883c98239 completed April 1, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d11029d3348190baf0dba766c4e960 completed April 4, 2026, 1:20 p.m.
NEDg Description generation batch_69d111113c5c81909ff654734b211753 completed April 4, 2026, 1:24 p.m.
NED2 Entity disambiguation (via description) batch_69d111ab40a48190bb77c1cf80ef87a8 completed April 4, 2026, 1:27 p.m.
Created at: March 30, 2026, 7:48 p.m.