Triple

T2030472
Position Surface form Disambiguated ID Type / Status
Subject Viljandi Culture Academy E44503 entity
Predicate hasCampus P116 FINISHED
Object Viljandi E225374 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: Viljandi | Statement: [Viljandi Culture Academy, hasCampus, Viljandi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viljandi
Context triple: [Viljandi Culture Academy, hasCampus, Viljandi]
  • A. Viljandi chosen
    Viljandi is a historic town in southern Estonia known for its medieval castle ruins, rich cultural life, and annual folk music festival.
  • B. Tartu
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • C. Viedma
    Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
  • D. Viipuri
    Viipuri is the Finnish name for Vyborg, a historically significant city and former Finnish cultural center now located in Russia near the Finnish border.
  • E. Narva
    Narva is a historic city in northeastern Estonia on the border with Russia, known for its strategic military importance and well-preserved fortress overlooking the Narva River.
  • 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_69a889144f2481909932f0746a93023d completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb915c9548190809d08c4d67466fb completed March 7, 2026, 5:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae270d7740819084f67c5f92a9995d completed March 9, 2026, 1:49 a.m.
Created at: March 4, 2026, 7:38 p.m.