Triple

T26704289
Position Surface form Disambiguated ID Type / Status
Subject Dmitry Shemyaka E673243 entity
Predicate sibling P363 FINISHED
Object Vasily Kosoy
Vasily Kosoy was a 15th-century Russian prince of the House of Moscow who briefly contested the grand princely throne during the dynastic struggles of the early Muscovite state.
E2293640 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: Vasily Kosoy | Statement: [Dmitry Shemyaka, sibling, Vasily Kosoy]
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: Vasily Kosoy
Triple: [Dmitry Shemyaka, sibling, Vasily Kosoy]
Generated description
Vasily Kosoy was a 15th-century Russian prince of the House of Moscow who briefly contested the grand princely throne during the dynastic struggles of the early Muscovite state.

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_69eecda2b49c8190a6c481cfc4c07954 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6178209548190aa912801975c105f completed May 2, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7ae7c101488190a192ba9bb8570486 completed Aug. 11, 2026, 9:13 a.m.
NEDg Description generation batch_6a7ae80cfb2081909b39746d64d4a675 completed Aug. 11, 2026, 9:14 a.m.
NED2 Entity disambiguation (via description) batch_6a7ae961cc708190ac3b20e200605c4e completed Aug. 11, 2026, 9:20 a.m.
Created at: April 27, 2026, 3:33 a.m.