Triple

T1381580
Position Surface form Disambiguated ID Type / Status
Subject Emden E29348 entity
Predicate hasTwinTown P919 FINISHED
Object Szczecin E27720 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: Szczecin | Statement: [Emden, hasTwinTown, Szczecin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Szczecin
Context triple: [Emden, hasTwinTown, Szczecin]
  • A. Szczecin chosen
    Szczecin is a large Polish city and important maritime and industrial center in northwestern Poland, situated near the Baltic Sea and the German border.
  • 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. Koszalin
    Koszalin is a city in northwestern Poland near the Baltic Sea, known as a regional cultural and economic center.
  • D. Gdynia
    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.
  • E. Kołobrzeg
    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.
  • 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_69a498d883a48190bfdca525296ef7ee completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c31b176c8190a896183140c5c8be completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69af2b42bb888190a0b16e3a59eb1175 completed March 9, 2026, 8:19 p.m.
Created at: March 1, 2026, 7:59 p.m.