Triple

T15624976
Position Surface form Disambiguated ID Type / Status
Subject The Last Station E375655 entity
Predicate character P662 FINISHED
Object Vladimir Chertkov
Vladimir Chertkov was a prominent Russian editor, publisher, and close disciple of Leo Tolstoy, known for his influential role in shaping and disseminating Tolstoyan ideas.
E1775198 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: Vladimir Chertkov | Statement: [The Last Station, character, Vladimir Chertkov]
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: Vladimir Chertkov
Triple: [The Last Station, character, Vladimir Chertkov]
Generated description
Vladimir Chertkov was a prominent Russian editor, publisher, and close disciple of Leo Tolstoy, known for his influential role in shaping and disseminating Tolstoyan ideas.

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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbaaf7608190888acf81a52e2f8a completed May 24, 2026, 8:49 a.m.
NEDg Description generation batch_6a12bce144b481909ef46950ddf8236a completed May 24, 2026, 8:54 a.m.
NED2 Entity disambiguation (via description) batch_6a12bd771268819080f52425e926c3bc completed May 24, 2026, 8:57 a.m.
Created at: April 10, 2026, 4:14 a.m.