Triple

T9700910
Position Surface form Disambiguated ID Type / Status
Subject Aegna E234771 entity
Predicate hasRegion P285 FINISHED
Object Northern Estonia E491062 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: Northern Estonia | Statement: [Aegna, hasRegion, Northern Estonia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Northern Estonia
Context triple: [Aegna, hasRegion, Northern Estonia]
  • A. northern Estonia chosen
    Northern Estonia is the region forming the northern part of the country of Estonia, encompassing the capital area and key economic and cultural centers along the Gulf of Finland.
  • B. Southern Estonia
    Southern Estonia is a region of Estonia known for its hilly landscapes, forests, and cultural center Tartu, the country’s second-largest city and main university town.
  • C. western Estonia
    Western Estonia is a coastal region of Estonia along the Baltic Sea, known for its islands, lighthouses, and maritime landscapes.
  • D. eastern Estonia
    Eastern Estonia is a geographical region of Estonia that includes areas such as Tartu County and is characterized by its cultural, educational, and economic significance centered around the city of Tartu.
  • E. Northern Latvia
    Northern Latvia is a scenic area of Latvia known for its forests, hills, and river valleys, including the course of the Gauja 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d70f55c8190934f37c25e9d4ba4 completed April 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1912e645881908d223a93f3ee61da completed April 4, 2026, 10:31 p.m.
Created at: March 30, 2026, 8:18 p.m.