Triple

T1688771
Position Surface form Disambiguated ID Type / Status
Subject Visegrád Group E36502 entity
Predicate foundingLocation P40 FINISHED
Object Visegrád E191366 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: Visegrád | Statement: [Visegrád Group, foundingLocation, Visegrád]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Visegrád
Context triple: [Visegrád Group, foundingLocation, Visegrád]
  • A. Visegrád chosen
    Visegrád is a historic town in northern Hungary on the Danube River, renowned for its medieval castle and royal palace that once served as a seat of Hungarian kings.
  • B. Pozsony
    Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
  • 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. Veszprém
    Veszprém is a historic city in western Hungary known for its medieval castle district and role as a regional cultural and administrative center.
  • E. Székesfehérvár
    Székesfehérvár is a historic city in central Hungary that served as a medieval royal seat and coronation site for Hungarian kings.
  • 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6296655c8190835ec0d20f7460ca completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebef5ac7c81908015969c04fcc425 completed March 9, 2026, 12:37 p.m.
Created at: March 4, 2026, 7:29 p.m.