Triple

T22288788
Position Surface form Disambiguated ID Type / Status
Subject SGD E550935 entity
Predicate nickname P55 FINISHED
Object Dynamo
Dynamo is a popular nickname for stochastic gradient descent (SGD), a fundamental optimization algorithm widely used to train machine learning models.
 E1527918 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: Dynamo | Statement: [SGD, nickname, Dynamo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dynamo
Context triple: [SGD, nickname, Dynamo]
  • A. Dynamo
    Dynamo is a prominent Russian sports club based in Moscow, best known for its professional football and ice hockey teams.
  • B. Dynamo
    Dynamo is the commonly used nickname for FC Dynamo Kyiv, one of Ukraine’s most successful and historically significant football clubs.
  • C. Dynamo
    Dynamo is the popular nickname of HC Pardubice, a professional ice hockey club based in Pardubice, Czech Republic.
  • D. Dynamo Diesel
    Dynamo Diesel is the bull-themed official mascot of the Houston Dynamo Major League Soccer team, known for energizing fans at matches and community events.
  • E. Dyme
    Dyme was an ancient Greek city-state in the region of Achaea, known as one of its earliest and westernmost poleis.
  • 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: Dynamo
Triple: [SGD, nickname, Dynamo]
Generated description
Dynamo is a popular nickname for stochastic gradient descent (SGD), a fundamental optimization algorithm widely used to train machine learning models.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dynamo
Target entity description: Dynamo is a popular nickname for stochastic gradient descent (SGD), a fundamental optimization algorithm widely used to train machine learning models.
  • A. Dynamo
    Dynamo is a prominent Russian sports club based in Moscow, best known for its professional football and ice hockey teams.
  • B. Dynamo
    Dynamo is the commonly used nickname for FC Dynamo Kyiv, one of Ukraine’s most successful and historically significant football clubs.
  • C. Dynamo
    Dynamo is the popular nickname of HC Pardubice, a professional ice hockey club based in Pardubice, Czech Republic.
  • D. Dynamo Diesel
    Dynamo Diesel is the bull-themed official mascot of the Houston Dynamo Major League Soccer team, known for energizing fans at matches and community events.
  • E. Dyme
    Dyme was an ancient Greek city-state in the region of Achaea, known as one of its earliest and westernmost poleis.
  • 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_69e11e45fb848190a1b2ae21296e3a5f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15609854c81908adb7681cff2c404 completed April 29, 2026, 12:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0abcafb5808190a3a43870466b89c2 completed May 18, 2026, 7:15 a.m.
NEDg Description generation batch_6a0abde18cc08190881f6dfecbcfd229 completed May 18, 2026, 7:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0abe349d488190bb7b09d44f5c0b33 completed May 18, 2026, 7:22 a.m.
Created at: April 16, 2026, 8:41 p.m.