Triple

T15127157
Position Surface form Disambiguated ID Type / Status
Subject South Karelian E361319 entity
Predicate closelyRelatedTo P37 FINISHED
Object Olonets Karelian E359876 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: Olonets Karelian | Statement: [South Karelian, closelyRelatedTo, Olonets Karelian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olonets Karelian
Context triple: [South Karelian, closelyRelatedTo, Olonets Karelian]
  • A. Olonets Karelian chosen
    Olonets Karelian is a major dialect of the Karelian language spoken primarily in the Republic of Karelia in northwestern Russia.
  • B. Ladoga Karelia
    Ladoga Karelia is a historical region in southeastern Finland, bordering Lake Ladoga, that was ceded to the Soviet Union after the Winter War.
  • C. Onega
    Onega is a small town in Arkhangelsk Oblast, northwestern Russia, situated near the mouth of the Onega River on the White Sea coast.
  • D. Onega River
    The Onega River is a major river in northwestern Russia that flows through the Karelia region before emptying into the White Sea.
  • E. White Sea Karelia
    White Sea Karelia is a coastal region of Karelia in northwestern Russia, characterized by its location along the White Sea and its sparsely populated, forested and maritime landscapes.
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005a1b9288190954f2d92549805e5 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69feb7f865c08190ab8fd15c14d0c06c completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 3:06 a.m.