Triple

T1641210
Position Surface form Disambiguated ID Type / Status
Subject Bay of Gdańsk E35474 entity
Predicate hasMajorPort P942 FINISHED
Object Gdańsk E18213 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: Gdańsk | Statement: [Bay of Gdańsk, hasMajorPort, Gdańsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gdańsk
Context triple: [Bay of Gdańsk, hasMajorPort, Gdańsk]
  • A. Gdańsk chosen
    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.
  • B. 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.
  • C. 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.
  • D. Koszalin
    Koszalin is a city in northwestern Poland near the Baltic Sea, known as a regional cultural and economic center.
  • E. Sopot
    Sopot is a suburban municipality of Belgrade, Serbia, known for its rural character and proximity to the Avala and Kosmaj mountains.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a3c883c8190bec1d87ecedf2575 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83294c4881908411bc4f8649dbdd completed March 10, 2026, 2:34 a.m.
Created at: March 4, 2026, 7:28 p.m.