Triple

T22370632
Position Surface form Disambiguated ID Type / Status
Subject Severny Vestnik E553029 entity
Predicate editor P1954 FINISHED
Object Lidia Veselitskaya
Lidia Veselitskaya was a Russian literary figure best known for her editorial work on the influential 19th-century journal Severny Vestnik, which helped shape the country’s intellectual and cultural life.
E1612477 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: Lidia Veselitskaya | Statement: [Severny Vestnik, editor, Lidia Veselitskaya]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lidia Veselitskaya
Triple: [Severny Vestnik, editor, Lidia Veselitskaya]
Generated description
Lidia Veselitskaya was a Russian literary figure best known for her editorial work on the influential 19th-century journal Severny Vestnik, which helped shape the country’s intellectual and cultural life.

Provenance (5 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_69e11e4c03248190a26a5060ea6973ee completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15803e7208190ba14c91fb90e15ca completed April 29, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e3711ac81908af3a33c06d04870 completed May 21, 2026, 9:50 p.m.
NEDg Description generation batch_6a0f7f21e3608190b646947083391923 completed May 21, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0f7fc9437c8190999551269a49fb65 completed May 21, 2026, 9:57 p.m.
Created at: April 16, 2026, 8:44 p.m.