Triple

T15062242
Position Surface form Disambiguated ID Type / Status
Subject Studenica school of painting E379656 entity
Predicate region P40 FINISHED
Object Raška E386940 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: Raška | Statement: [Studenica school of painting, region, Raška]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Raška
Context triple: [Studenica school of painting, region, Raška]
  • A. Raška chosen
    Raška is a historical region in southwestern Serbia regarded as the medieval heartland of the early Serbian state and Orthodox monastic culture.
  • B. Kraljevo
    Kraljevo is a city in central Serbia known as a regional administrative and cultural center, situated near several important medieval Serbian monasteries.
  • C. Niš
    Niš is one of the largest and oldest cities in Serbia, known as a key cultural, economic, and transportation hub in the southern part of the country.
  • D. Kragujevac
    Kragujevac is a central Serbian city historically significant as an early capital and industrial and cultural hub of the country.
  • E. Užice
    Užice is a city in western Serbia known as a regional industrial and cultural center situated along the Đetinja River and surrounded by mountainous terrain.
  • 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_69d85cd7683881908d405c1b5d7b4f7f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dedee6a55c8190b40c4672fb46b79b completed April 15, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff677b7be08190afc2767835836908 completed May 9, 2026, 4:57 p.m.
Created at: April 10, 2026, 3:02 a.m.