Triple

T15372959
Position Surface form Disambiguated ID Type / Status
Subject Mulgi dialect E367594 entity
Predicate historicalRegion P915 FINISHED
Object Pärnu County E693922 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: Pärnu County | Statement: [Mulgi dialect, historicalRegion, Pärnu County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pärnu County
Context triple: [Mulgi dialect, historicalRegion, Pärnu County]
  • A. Pärnu County chosen
    Pärnu County is an administrative region in southwestern Estonia known for its coastal landscapes and the resort city of Pärnu.
  • B. 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.
  • C. Võru County
    Võru County is a rural region in southeastern Estonia known for its distinct South Estonian (Võro) linguistic and cultural heritage.
  • D. 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.
  • E. Ida-Viru County
    Ida-Viru County is an administrative region in northeastern Estonia known for its industrial centers, oil shale industry, and significant Russian-speaking population.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e5c1d548190930bfaf0861595ae completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f2754648190bfd0bd15f20b40d2 completed May 9, 2026, 4:21 p.m.
Created at: April 10, 2026, 3:18 a.m.