Triple

T11173164
Position Surface form Disambiguated ID Type / Status
Subject Arthur Greiser E264334 entity
Predicate placeOfDeath P21 FINISHED
Object Poznań E14540 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: Poznań | Statement: [Arthur Greiser, placeOfDeath, Poznań]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Poznań
Context triple: [Arthur Greiser, placeOfDeath, Poznań]
  • A. Poznań chosen
    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.
  • B. 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.
  • C. Bydgoszcz
    Bydgoszcz is a major city in northern Poland known as an important economic, cultural, and academic center on the Brda and Vistula rivers.
  • D. Opole
    Opole is a historic city in southwestern Poland, known as one of the country’s oldest urban centers and a regional cultural hub.
  • E. Kraków
    Kraków is one of Poland’s oldest and most historically significant cities, renowned for its well-preserved medieval core, royal heritage, and cultural institutions.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e89660208190b1d9e91529f5d246 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c1d31048190ab0a8d8e00515211 completed May 8, 2026, 2:36 a.m.
Created at: April 8, 2026, 9:29 p.m.