Triple

T8478147
Position Surface form Disambiguated ID Type / Status
Subject Janus Pannonius Museum E200446 entity
Predicate headquartersLocation P62 FINISHED
Object Pécs city centre E38480 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: Pécs city centre | Statement: [Janus Pannonius Museum, headquartersLocation, Pécs city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pécs city centre
Context triple: [Janus Pannonius Museum, headquartersLocation, Pécs city centre]
  • A. Pécs chosen
    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.
  • B. Siófok
    Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
  • C. Esztergom
    Esztergom is a historic Hungarian city on the Danube River that served as an early royal capital and remains a major religious and cultural center.
  • D. Gödöllő
    Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
  • 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_69ca831b17988190a1f3f3413d57b820 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5216d6481908e25a49bcc2e00cc completed March 31, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce88c89a9081908445bbc531f500c9 completed April 2, 2026, 3:18 p.m.
Created at: March 30, 2026, 6:12 p.m.