Triple

T14865375
Position Surface form Disambiguated ID Type / Status
Subject Gresham Palace E349601 entity
Predicate facing P1699 FINISHED
Object Széchenyi István tér E719016 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: Széchenyi István tér | Statement: [Gresham Palace, facing, Széchenyi István tér]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Széchenyi István tér
Context triple: [Gresham Palace, facing, Széchenyi István tér]
  • A. Széchenyi István tér chosen
    Széchenyi István tér is a prominent square in central Budapest, Hungary, known for its grand riverside location by the Danube and its surrounding historic and cultural landmarks.
  • B. Szent István tér
    Szent István tér is a central public square in Pécs, Hungary, known for its historic surroundings and cultural attractions.
  • C. Széll Kálmán tér
    Széll Kálmán tér is a major public square and key transport hub in Budapest, serving as an interchange for metro, tram, and bus lines on the Buda side of the city.
  • D. Liszt Ferenc tér
    Liszt Ferenc tér is a popular square in central Budapest known for its lively café culture, restaurants, and proximity to the Liszt Academy of Music.
  • E. Rákóczi tér
    Rákóczi tér is a public square and transport hub in Budapest known for its central location and metro station in the Józsefváros district.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5761c688190b4477cb081554b51 completed April 15, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69febfd1a1b48190b3b69b2841f643a3 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 1:55 a.m.