Triple

T27445852
Position Surface form Disambiguated ID Type / Status
Subject Anatoly Kvashnin E692276 entity
Predicate name P16 FINISHED
Object Anatoly Vasilyevich Kvashnin
Anatoly Vasilyevich Kvashnin was a Russian Army general who served as Chief of the General Staff of the Armed Forces of the Russian Federation from 1997 to 2004.
 E2294536 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: Anatoly Vasilyevich Kvashnin | Statement: [Anatoly Kvashnin, name, Anatoly Vasilyevich Kvashnin]
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: Anatoly Vasilyevich Kvashnin
Triple: [Anatoly Kvashnin, name, Anatoly Vasilyevich Kvashnin]
Generated description
Anatoly Vasilyevich Kvashnin was a Russian Army general who served as Chief of the General Staff of the Armed Forces of the Russian Federation from 1997 to 2004.

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_69ef5206c9248190b5975c2a7f9d229c completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62d920bfc8190b5b669c491a05b24 completed May 2, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7bf98067188190a2650127633ee9a2 completed Aug. 12, 2026, 4:41 a.m.
NEDg Description generation batch_6a7bf9e756d88190bc8bfb7fca72a918 completed Aug. 12, 2026, 4:43 a.m.
NED2 Entity disambiguation (via description) batch_6a7bfa3e0b3c81908eb5330200e622b0 completed Aug. 12, 2026, 4:44 a.m.
Created at: April 27, 2026, 12:46 p.m.