Triple

T5853002
Position Surface form Disambiguated ID Type / Status
Subject Wernigerode E130080 entity
Predicate hasTwinTown P919 FINISHED
Object Kołobrzeg E180362 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: Kołobrzeg | Statement: [Wernigerode, hasTwinTown, Kołobrzeg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kołobrzeg
Context triple: [Wernigerode, hasTwinTown, Kołobrzeg]
  • A. Kołobrzeg chosen
    Kołobrzeg is a historic Polish port and spa city on the Baltic Sea, known for its beaches, seaside resorts, and role as a popular tourist destination.
  • B. Koszalin
    Koszalin is a city in northwestern Poland near the Baltic Sea, known as a regional cultural and economic center.
  • C. Elbląg
    Elbląg is a historic city in northern Poland known for its reconstructed Old Town, medieval heritage, and role as an important port and industrial center.
  • D. Szczecin
    Szczecin is a large Polish city and important maritime and industrial center in northwestern Poland, situated near the Baltic Sea and the German border.
  • E. Bydgoszcz
    Bydgoszcz is a major city in northern Poland known as an important economic, cultural, and academic center on the Brda and Vistula rivers.
  • 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_69c0084de39081909eb34e6bed74215a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0355038008190bf38980349b533e2 completed March 22, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1b8f8508190942ce1725884d254 completed March 23, 2026, 2:13 a.m.
Created at: March 22, 2026, 3:55 p.m.