Triple

T31474986
Position Surface form Disambiguated ID Type / Status
Subject Mercury City Tower E802966 entity
Predicate owner P347 FINISHED
Object Igor Kesaev
Igor Kesaev is a Russian billionaire businessman and tobacco magnate with significant investments in real estate and retail.
E2252035 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: Igor Kesaev | Statement: [Mercury City Tower, owner, Igor Kesaev]
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: Igor Kesaev
Triple: [Mercury City Tower, owner, Igor Kesaev]
Generated description
Igor Kesaev is a Russian billionaire businessman and tobacco magnate with significant investments in real estate and retail.

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_69f348c9477c8190bc0a21f6d482d2fc completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a17f37a48190b4ccd0c45ddafe6c completed May 3, 2026, 1:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a412c8b39e48190a37e7f33c71ac3ba completed June 28, 2026, 2:15 p.m.
NEDg Description generation batch_6a41485ed9408190be9b332e9ef1a7ba completed June 28, 2026, 4:14 p.m.
NED2 Entity disambiguation (via description) batch_6a4148e1e0688190b805d526b437c280 completed June 28, 2026, 4:16 p.m.
Created at: April 30, 2026, 9:28 p.m.