Triple

T16389935
Position Surface form Disambiguated ID Type / Status
Subject K2 assault rifle E398022 entity
Predicate manufacturer P490 FINISHED
Object S&T Motiv
S&T Motiv is a South Korean defense company known for designing and producing small arms and other military weapons systems.
 E1209933 NE FINISHED

How this triple was built (4 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: S&T Motiv | Statement: [K2 assault rifle, manufacturer, S&T Motiv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S&T Motiv
Context triple: [K2 assault rifle, manufacturer, S&T Motiv]
  • A. Dinas Mot
    Dinas Mot is a prominent rock formation in Snowdonia, Wales, renowned for its classic multi-pitch traditional climbing routes.
  • B. MOTC
    MOTC is the government ministry in Taiwan responsible for overseeing national transportation systems and communications infrastructure.
  • C. Motok
    The Motok are an indigenous ethnic community of Upper Assam in northeastern India, known for their distinct cultural traditions and historical presence in the region.
  • D. Nomentum
    Nomentum was an ancient town in Latium, northeast of Rome, known as a minor but historically significant settlement along important Roman roads.
  • E. Laudamotion
    Laudamotion was an Austrian low-cost airline established by former Formula One champion Niki Lauda.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: S&T Motiv
Triple: [K2 assault rifle, manufacturer, S&T Motiv]
Generated description
S&T Motiv is a South Korean defense company known for designing and producing small arms and other military weapons systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: S&T Motiv
Target entity description: S&T Motiv is a South Korean defense company known for designing and producing small arms and other military weapons systems.
  • A. Dinas Mot
    Dinas Mot is a prominent rock formation in Snowdonia, Wales, renowned for its classic multi-pitch traditional climbing routes.
  • B. MOTC
    MOTC is the government ministry in Taiwan responsible for overseeing national transportation systems and communications infrastructure.
  • C. Motok
    The Motok are an indigenous ethnic community of Upper Assam in northeastern India, known for their distinct cultural traditions and historical presence in the region.
  • D. Nomentum
    Nomentum was an ancient town in Latium, northeast of Rome, known as a minor but historically significant settlement along important Roman roads.
  • E. Laudamotion
    Laudamotion was an Austrian low-cost airline established by former Formula One champion Niki Lauda.
  • F. None of above. chosen

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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e326414f44819093ebc11f1b63444c completed April 18, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00357167b881909a5182537ef973ce completed May 10, 2026, 7:36 a.m.
NEDg Description generation batch_6a003659af2481908ccf0cc65b673b8f completed May 10, 2026, 7:40 a.m.
NED2 Entity disambiguation (via description) batch_6a0037957d7c81908b517ebea0b70a5b completed May 10, 2026, 7:45 a.m.
Created at: April 10, 2026, 5:08 a.m.