Triple

T20045822
Position Surface form Disambiguated ID Type / Status
Subject Sukhoi Su-35S E497554 entity
Predicate manufacturer P490 FINISHED
Object Sukhoi NE NERFINISHED

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: Sukhoi | Statement: [Sukhoi Su-35S, manufacturer, Sukhoi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sukhoi
Context triple: [Sukhoi Su-35S, manufacturer, Sukhoi]
  • A. OKB Sukhoi chosen
    OKB Sukhoi is a major Russian aerospace design bureau renowned for developing a wide range of military aircraft, including advanced fighter jets and bombers.
  • B. Ilyushin
    Ilyushin is a Soviet and later Russian aircraft design bureau best known for producing a wide range of military and civilian airliners and transport aircraft used extensively across Eastern Bloc countries.
  • C. Tupolev
    Tupolev is a Russian aerospace and defense company best known for designing and producing military and civilian aircraft, including strategic bombers and airliners.
  • D. Sukhoi Su-31
    The Sukhoi Su-31 is a Russian single-seat aerobatic aircraft renowned for its high maneuverability and use in advanced competition flying.
  • E. Su-39
    The Su-39 is a modernized Russian close air support and anti-tank aircraft developed from the Su-25, featuring enhanced avionics and weapon systems for improved battlefield effectiveness.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da627278c88190babe4297a9df1236 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6632a5e888190ade41657ffd057f6 completed April 20, 2026, 5:32 p.m.
Created at: April 11, 2026, 3:37 p.m.