Triple

T14367861
Position Surface form Disambiguated ID Type / Status
Subject Coloman of Hungary E356281 entity
Predicate burialPlace P196 FINISHED
Object Székesfehérvár E3113 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: Székesfehérvár | Statement: [Coloman of Hungary, burialPlace, Székesfehérvár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Székesfehérvár
Context triple: [Coloman of Hungary, burialPlace, Székesfehérvár]
  • A. Székesfehérvár chosen
    Székesfehérvár is a historic city in central Hungary that served as a medieval royal seat and coronation site for Hungarian kings.
  • B. Gyulafehérvár
    Gyulafehérvár, known today as Alba Iulia in Romania, is a historic city that served as the political and cultural center of Transylvania for centuries.
  • C. Szekesfehervar
    Szekesfehérvár is a historic city in central Hungary that served as a medieval royal seat and coronation site for Hungarian kings.
  • 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. Budavár
    Budavár is the historic Buda Castle quarter of Budapest, known for its medieval streets, royal palace complex, and panoramic views over the Danube.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8faf00e8819087d7100e9d8c1877 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ebeb5ec8190afef40d87c74a8a0 completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 1:15 a.m.