Triple

T29469377
Position Surface form Disambiguated ID Type / Status
Subject The Sentimental Policeman E747468 entity
Predicate composer P1361 FINISHED
Object Oleg Karavajchuk
Oleg Karavajchuk was an eccentric and innovative Russian composer and pianist known for his highly original, improvisational music and collaborations with Soviet and post-Soviet cinema and theater.
E1885633 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: Oleg Karavajchuk | Statement: [The Sentimental Policeman, composer, Oleg Karavajchuk]
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: Oleg Karavajchuk
Triple: [The Sentimental Policeman, composer, Oleg Karavajchuk]
Generated description
Oleg Karavajchuk was an eccentric and innovative Russian composer and pianist known for his highly original, improvisational music and collaborations with Soviet and post-Soviet cinema and theater.

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_69f0bd42cf308190bb01b20bc5b7c2d0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66baa0d3081908a4760782d8f533a completed May 2, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26e5d369f48190a2c81d8c6d43af6e completed June 8, 2026, 3:54 p.m.
NEDg Description generation batch_6a26e6776f9481908df0bc905c664756 completed June 8, 2026, 3:57 p.m.
NED2 Entity disambiguation (via description) batch_6a26e7abb57c819095ad0e1dbf8a9be8 completed June 8, 2026, 4:02 p.m.
Created at: April 28, 2026, 3:56 p.m.