Triple

T25609745
Position Surface form Disambiguated ID Type / Status
Subject Foliant program E642014 entity
Predicate successorState P3025 FINISHED
Object Russian Federation E10011 NE FINISHED

How this triple was built (1 step)

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: Russian Federation | Statement: [Foliant program, successorState, Russian Federation]

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_69e75dc6ccf081908d49578fd36a76d5 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f9e1f1408190bab690f67f7d3a31 completed May 2, 2026, 1:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11271e15f08190a6f8526fa979c19b completed May 23, 2026, 4:03 a.m.
Created at: April 21, 2026, 4:40 p.m.