Triple

T31413432
Position Surface form Disambiguated ID Type / Status
Subject Stroganov estates in Perm Governorate E801328 entity
Predicate hasPart P35 FINISHED
Object Krasnovishersk estate
Krasnovishersk estate was a rural property in the Perm Governorate historically owned and developed by the influential Stroganov family.
E1964983 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: Krasnovishersk estate | Statement: [Stroganov estates in Perm Governorate, hasPart, Krasnovishersk estate]
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: Krasnovishersk estate
Triple: [Stroganov estates in Perm Governorate, hasPart, Krasnovishersk estate]
Generated description
Krasnovishersk estate was a rural property in the Perm Governorate historically owned and developed by the influential Stroganov family.

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_69f348c0dd648190bf2fd7642f78eb06 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a08e47dc8190a0676a05011d3e69 completed May 3, 2026, 1:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b1446bff88190bd02e2e4a16216cd completed June 11, 2026, 8:02 p.m.
NEDg Description generation batch_6a2b1b6b29088190b7733f428ef0209b completed June 11, 2026, 8:32 p.m.
NED2 Entity disambiguation (via description) batch_6a2b1c49659c819084fbe6b239adffcf completed June 11, 2026, 8:36 p.m.
Created at: April 30, 2026, 8:41 p.m.