Triple

T5034905
Position Surface form Disambiguated ID Type / Status
Subject Transdanubia E113398 entity
Predicate containsCity P294 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: [Transdanubia, containsCity, Székesfehérvár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Székesfehérvár
Context triple: [Transdanubia, containsCity, 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. Veszprém
    Veszprém is a historic city in western Hungary known for its medieval castle district and role as a regional cultural and administrative center.
  • D. Budavár
    Budavár is the historic Buda Castle quarter of Budapest, known for its medieval streets, royal palace complex, and panoramic views over the Danube.
  • E. 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.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73b8646c8190b3cc20193e4639ee completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea477efec8190a84a0186f5517a43 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:36 p.m.