Triple

T12741587
Position Surface form Disambiguated ID Type / Status
Subject Péter Pázmány E304500 entity
Predicate placeOfDeath P21 FINISHED
Object Pozsony E126688 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: Pozsony | Statement: [Péter Pázmány, placeOfDeath, Pozsony]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pozsony
Context triple: [Péter Pázmány, placeOfDeath, Pozsony]
  • A. Pozsony chosen
    Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
  • B. Veszprém
    Veszprém is a historic city in western Hungary known for its medieval castle district and role as a regional cultural and administrative center.
  • C. Pécs
    Pécs is a historic cultural and university city in southwestern Hungary, renowned for its Roman and Ottoman heritage and its designation as a European Capital of Culture in 2010.
  • D. Győr
    Győr is a historic city in northwestern Hungary, known as an important regional cultural and economic center at the confluence of the Danube, Rába, and Rábca rivers.
  • E. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9646dfc908190bc398935d1d23537 completed April 10, 2026, 8:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78ac916748190821c0cdabe54fcbc completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 5:26 p.m.