Triple

T14210352
Position Surface form Disambiguated ID Type / Status
Subject István Széchenyi E352210 entity
Predicate workLocation P7 FINISHED
Object Buda E70138 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: Buda | Statement: [István Széchenyi, workLocation, Buda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buda
Context triple: [István Széchenyi, workLocation, Buda]
  • A. Buda chosen
    Buda is the historic western part of modern-day Budapest, known for its hilly landscape, medieval castle district, and role as a former capital of the Kingdom of Hungary.
  • B. Buda
    Buda is a small but rapidly growing city in Central Texas, located just south of Austin and known for its historic downtown and community events.
  • C. Bud’da
    Bud’da is an American hip-hop record producer known for his work with prominent rap artists in the late 1990s and early 2000s.
  • D. Buda Bari
    Buda Bari is one of the historic city gates of Harar Jugol, the fortified old town of Harar in eastern Ethiopia.
  • E. Bodhi
    Bodhi is the charismatic, thrill-seeking surfer and bank robber who serves as the philosophical antagonist to FBI agent Johnny Utah in the film "Point Break."
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61fa8d24819092a8ec5d34c1c799 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c29b4e08190896ddde5096628d3 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:05 a.m.