Triple

T28029837
Position Surface form Disambiguated ID Type / Status
Subject Misha Alperin E708233 entity
Predicate fullName P16 FINISHED
Object Mikhail Alperin
Mikhail Alperin was a Moldovan-born jazz pianist and composer known for blending Eastern European folk music with contemporary jazz, notably as a member of the Moscow Art Trio.
E1892843 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: Mikhail Alperin | Statement: [Misha Alperin, fullName, Mikhail Alperin]
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: Mikhail Alperin
Triple: [Misha Alperin, fullName, Mikhail Alperin]
Generated description
Mikhail Alperin was a Moldovan-born jazz pianist and composer known for blending Eastern European folk music with contemporary jazz, notably as a member of the Moscow Art Trio.

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_69ef9b6bdd9c8190bb3a574a03774ad1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63c7164e48190a40df492718b3e3c completed May 2, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2713e9c4848190bedfc575e8eeeea0 completed June 8, 2026, 7:11 p.m.
NEDg Description generation batch_6a2714fad8188190bf86af12ee777b53 completed June 8, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_6a27198a097c8190aea66eba80acc1d8 completed June 8, 2026, 7:35 p.m.
Created at: April 27, 2026, 8:15 p.m.