Triple

T34282978
Position Surface form Disambiguated ID Type / Status
Subject Vladimir Kagan E879645 entity
Predicate employer P7 FINISHED
Object Vladimir Kagan Design Group
Vladimir Kagan Design Group is a furniture and interior design firm known for producing the iconic, sculptural modernist pieces created by designer Vladimir Kagan.
E253700 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 Kagan Design Group | Statement: [Vladimir Kagan, employer, Vladimir Kagan Design Group]
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 Kagan Design Group
Triple: [Vladimir Kagan, employer, Vladimir Kagan Design Group]
Generated description
Vladimir Kagan Design Group is a furniture and interior design firm known for producing the iconic, sculptural modernist pieces created by designer Vladimir Kagan.

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_69f349b5f6648190b9420d94a4cd16e0 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f712f0553081909bc238825c002d9e completed May 3, 2026, 9:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36e62e0bdc819081b25e12199f4624 completed June 20, 2026, 7:12 p.m.
NEDg Description generation batch_6a36e9f0691c8190b965d5010f2db72a completed June 20, 2026, 7:28 p.m.
NED2 Entity disambiguation (via description) batch_6a36ea5fa120819093233c84e6e833df completed June 20, 2026, 7:30 p.m.
Created at: May 1, 2026, 1:57 a.m.