Triple

T9274607
Position Surface form Disambiguated ID Type / Status
Subject Southern Estonia E222913 entity
Predicate hasRegion P285 FINISHED
Object Viljandi County E727852 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 County | Statement: [Southern Estonia, hasRegion, Viljandi County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viljandi County
Context triple: [Southern Estonia, hasRegion, Viljandi County]
  • A. Viljandi County chosen
    Viljandi County is a rural administrative region in southern Estonia known for its lakes, forests, and historic town of Viljandi.
  • B. Põlva County
    Põlva County is a rural administrative region in southeastern Estonia known for its forests, lakes, and strong South Estonian cultural and linguistic heritage.
  • C. Järva County
    Järva County is a historical and administrative region in central Estonia known for its rural landscapes and small towns.
  • D. Tartu County
    Tartu County is an administrative region in eastern Estonia centered around the university city of Tartu and known for its cultural, educational, and economic significance.
  • E. Lääne-Viru County
    Lääne-Viru County is a northeastern administrative region of Estonia known for its coastal landscapes, historic manors, and the town of Rakvere.
  • 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_69ca841ffe208190aa7bcffbef2f8379 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd078a045c8190b2c4d1ec64b932ad completed April 1, 2026, 11:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69d100bcd1d08190ad8fe83841f6761f completed April 4, 2026, 12:14 p.m.
Created at: March 30, 2026, 7:33 p.m.