Triple

T940048
Position Surface form Disambiguated ID Type / Status
Subject Pomerania E20284 entity
Predicate containsCity P294 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: [Pomerania, containsCity, Szczecin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Szczecin
Context triple: [Pomerania, containsCity, 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. 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.
  • D. Sopot
    Sopot is a Polish Baltic Sea resort city famous for its sandy beaches, long wooden pier, and vibrant spa and nightlife culture.
  • E. Toruń
    Toruń is a historic city in northern Poland, renowned for its well-preserved medieval Old Town and as the birthplace of astronomer Nicolaus Copernicus.
  • 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_69a493b0270c81909e6c9ce310f6aa55 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b38b7da08190ac0853655dab678a completed March 1, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad230d2870819099001561e36078f5 completed March 8, 2026, 7:19 a.m.
Created at: March 1, 2026, 7:40 p.m.