Triple

T2916960
Position Surface form Disambiguated ID Type / Status
Subject Orłowo E78629 entity
Predicate locatedIn P40 FINISHED
Object Gdynia E12134 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: Gdynia | Statement: [Orłowo, locatedIn, Gdynia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gdynia
Context triple: [Orłowo, locatedIn, Gdynia]
  • A. Gdynia chosen
    Gdynia is a major seaport city on Poland’s Baltic coast, developed rapidly in the 20th century into one of the country’s key maritime and economic centers.
  • B. Gdańsk
    Gdańsk is a major Polish port city on the Baltic Sea, known for its rich Hanseatic history, shipyards, and role in the origins of the Solidarity movement.
  • C. Bydgoszcz
    Bydgoszcz is a major city in northern Poland known as an important economic, cultural, and academic center on the Brda and Vistula rivers.
  • 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. Koszalin
    Koszalin is a city in northwestern Poland near the Baltic Sea, known as a regional cultural and economic 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_69ad8b0c2ad081909ff87050ae542bb9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad96a2bdd88190aa01c26a27f9afbd completed March 8, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b67b92d4dc81908a26a977bc25319c completed March 15, 2026, 9:27 a.m.
Created at: March 8, 2026, 2:53 p.m.