Triple

T577234
Position Surface form Disambiguated ID Type / Status
Subject Motorola Mobility E13781 entity
Predicate brand P1500 FINISHED
Object Moto
Moto is a consumer electronics brand used by Motorola Mobility for its line of smartphones and related mobile devices.
 E72299 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: Moto | Statement: [Motorola Mobility, brand, Moto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Moto
Context triple: [Motorola Mobility, brand, Moto]
  • A. Flivver
    Flivver is a colloquial nickname for the Ford Model T, the iconic early 20th-century mass-produced automobile that revolutionized personal transportation.
  • B. Velo
    Velo is a nicotine pouch brand owned by British American Tobacco, marketed as a smokeless alternative to traditional cigarettes.
  • C. Kawasaki
    Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
  • D. Mvezo
    Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
  • E. Rider
    Rider is a cross-platform integrated development environment by JetBrains, widely used for .NET and C# development.
  • 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: Moto
Triple: [Motorola Mobility, brand, Moto]
Generated description
Moto is a consumer electronics brand used by Motorola Mobility for its line of smartphones and related mobile devices.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Moto
Target entity description: Moto is a consumer electronics brand used by Motorola Mobility for its line of smartphones and related mobile devices.
  • A. Flivver
    Flivver is a colloquial nickname for the Ford Model T, the iconic early 20th-century mass-produced automobile that revolutionized personal transportation.
  • B. Velo
    Velo is a nicotine pouch brand owned by British American Tobacco, marketed as a smokeless alternative to traditional cigarettes.
  • C. Kawasaki
    Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
  • D. Mvezo
    Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
  • E. Rider
    Rider is a cross-platform integrated development environment by JetBrains, widely used for .NET and C# development.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b68cc808190b1ba45bdad78443d completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a501bfb6408190bf7e1f462f39723d completed March 2, 2026, 3:19 a.m.
NEDg Description generation batch_69a5026c35408190ab22dab86c673e0f completed March 2, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69a5063ad6b481909537a97e6a81eaa4 completed March 2, 2026, 3:38 a.m.
Created at: March 1, 2026, 7:33 p.m.