Triple

T133362
Position Surface form Disambiguated ID Type / Status
Subject Baltic Sea E2697 entity
Predicate majorPort P528 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: [Baltic Sea, majorPort, Gdynia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gdynia
Context triple: [Baltic Sea, majorPort, 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. Wrocław
    Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
  • D. Poznań
    Poznań is a historic and economically significant city in western Poland, known for its medieval Old Town, role as an early center of Polish statehood, and status as a major academic and industrial hub.
  • E. Łódź
    Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing 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_69a2520c0f3481908b0ed054a2fca8d0 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a25788b2688190a45b39447f702551 completed Feb. 28, 2026, 2:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69a33e3bf8948190a30af36f4c21eded completed Feb. 28, 2026, 7:13 p.m.
Created at: Feb. 28, 2026, 2:30 a.m.