Triple

T23151925
Position Surface form Disambiguated ID Type / Status
Subject Ilyushin Il-76 E578343 entity
Predicate designedBy P184 FINISHED
Object Genrikh Novozhilov
Genrikh Novozhilov was a prominent Soviet aircraft designer and chief designer at the Ilyushin Design Bureau, known for leading the development of major military and civilian transport aircraft.
E1683949 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: Genrikh Novozhilov | Statement: [Ilyushin Il-76, designedBy, Genrikh Novozhilov]
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: Genrikh Novozhilov
Triple: [Ilyushin Il-76, designedBy, Genrikh Novozhilov]
Generated description
Genrikh Novozhilov was a prominent Soviet aircraft designer and chief designer at the Ilyushin Design Bureau, known for leading the development of major military and civilian transport aircraft.

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_69e245fb8de081908f0eba7b5fd75bc4 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18ef982488190984a6358bdcd577c completed April 29, 2026, 4:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad1b164c81909e374fa0b402f137 completed May 22, 2026, 7:23 p.m.
NEDg Description generation batch_6a10aeae38748190a970045e9bbd49f7 completed May 22, 2026, 7:29 p.m.
NED2 Entity disambiguation (via description) batch_6a10af62078481908759f9df2167d81f completed May 22, 2026, 7:32 p.m.
Created at: April 17, 2026, 4:01 p.m.