Triple

T8662068
Position Surface form Disambiguated ID Type / Status
Subject Jakovali Hassan Mosque E205571 entity
Predicate locatedIn P40 FINISHED
Object Baranya County E199407 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: Baranya County | Statement: [Jakovali Hassan Mosque, locatedIn, Baranya County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baranya County
Context triple: [Jakovali Hassan Mosque, locatedIn, Baranya County]
  • A. Baranya County chosen
    Baranya County is an administrative region in southern Hungary known for its cultural center Pécs, wine-producing areas, and diverse natural landscapes.
  • B. Veszprém County
    Veszprém County is an administrative region in western Hungary known for its historic city of Veszprém and its location along the northern shore of Lake Balaton.
  • C. Zala County
    Zala County is an administrative region in southwestern Hungary known for its rolling hills, thermal spas, and proximity to Lake Balaton and the Croatian border.
  • D. Sümeg District
    Sümeg District is an administrative district in western Hungary, located within Veszprém County and centered around the town of Sümeg.
  • E. Heves County
    Heves County is an administrative region in northern Hungary known for its natural landscapes, including part of the Mátra mountain range, and historic towns such as Eger.
  • 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_69ca8350897c819086cde7596fbe5fe7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4872a190819087d679f3006bd030 completed March 31, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef37efbf08190805fbb270a4bce37 completed April 2, 2026, 10:53 p.m.
Created at: March 30, 2026, 6:30 p.m.