Triple

T15630014
Position Surface form Disambiguated ID Type / Status
Subject Oprichnina E375785 entity
Predicate significantFigure P428 FINISHED
Object Aleksei Basmanov
Aleksei Basmanov was a prominent 16th-century Russian noble and military leader who became one of Tsar Ivan the Terrible’s key enforcers during the era of the Oprichnina.
E1781707 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: Aleksei Basmanov | Statement: [Oprichnina, significantFigure, Aleksei Basmanov]
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: Aleksei Basmanov
Triple: [Oprichnina, significantFigure, Aleksei Basmanov]
Generated description
Aleksei Basmanov was a prominent 16th-century Russian noble and military leader who became one of Tsar Ivan the Terrible’s key enforcers during the era of the Oprichnina.

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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04eb536348190b93ed3c178d1ffb8 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0a179d081909d8e3369afb277f0 completed May 24, 2026, 10:19 a.m.
NEDg Description generation batch_6a12d169e8888190bf3c8e7f0718a3a5 completed May 24, 2026, 10:22 a.m.
NED2 Entity disambiguation (via description) batch_6a12d23dc1b48190aa7f52797b82db62 completed May 24, 2026, 10:26 a.m.
Created at: April 10, 2026, 4:14 a.m.