Triple

T1369035
Position Surface form Disambiguated ID Type / Status
Subject Günter Grass E30068 entity
Predicate placeOfBirth P1 FINISHED
Object Danzig 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: Danzig | Statement: [Günter Grass, placeOfBirth, Danzig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danzig
Context triple: [Günter Grass, placeOfBirth, Danzig]
  • 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. Malbork
    Malbork is a historic town in northern Poland best known for the vast medieval Malbork Castle, one of the largest brick castles in the world and a UNESCO World Heritage Site.
  • D. Wilno
    Wilno is the historical Polish name for Vilnius, a major cultural and political center of the region that served as an important city in the interwar Second Polish Republic.
  • E. 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.
  • 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c2d60fdc8190a9954b74ca2b2541 completed March 1, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69af173cc94c8190a351334e7645cc0c completed March 9, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:57 p.m.