Triple

T9064237
Position Surface form Disambiguated ID Type / Status
Subject Egentliga Finland E217202 entity
Predicate containsMunicipality P852 FINISHED
Object Rusko E233032 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: Rusko | Statement: [Egentliga Finland, containsMunicipality, Rusko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rusko
Context triple: [Egentliga Finland, containsMunicipality, Rusko]
  • A. Rusko chosen
    Rusko is a small municipality in southwestern Finland known for its rural character and proximity to the city of Turku.
  • B. Rus'
    Rus' was a medieval East Slavic state that emerged in Eastern Europe and laid the foundations for the later Russian, Ukrainian, and Belarusian nations.
  • C. Rusa
    Rusa is a genus of deer native to South and Southeast Asia, including species such as the Javan rusa and sambar.
  • D. Russas
    Russas is a municipality in the northeastern Brazilian state of Ceará, known for its agricultural activities and semi-arid climate.
  • E. Russia
    Russia is the world’s largest country by land area, spanning Eastern Europe and northern Asia and exerting major political, military, and cultural influence globally.
  • 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_69ca83d5a7f48190b16c1e59bd43ede0 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc94bb26588190b7d6f2d70819e86f completed April 1, 2026, 3:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d065bddf1c81909b6134179fe92556 completed April 4, 2026, 1:13 a.m.
Created at: March 30, 2026, 7:11 p.m.