Triple

T15532252
Position Surface form Disambiguated ID Type / Status
Subject Large-Scale Machine Learning with Stochastic Gradient Descent E370247 entity
Predicate hasAbbreviation P43 FINISHED
Object SGD (for stochastic gradient descent in the title) E370247 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: SGD (for stochastic gradient descent in the title) | Statement: [Large-Scale Machine Learning with Stochastic Gradient Descent, hasAbbreviation, SGD (for stochastic gradient descent in the title)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SGD (for stochastic gradient descent in the title)
Context triple: [Large-Scale Machine Learning with Stochastic Gradient Descent, hasAbbreviation, SGD (for stochastic gradient descent in the title)]
  • A. “Stochastic Gradient Descent Tricks”
    “Stochastic Gradient Descent Tricks” is a well-known paper by Léon Bottou that surveys practical techniques and heuristics for effectively applying stochastic gradient descent in machine learning.
  • B. SGD
    SGD is the official currency code for the Singapore dollar, the national currency of Singapore used in domestic and international transactions.
  • C. SGD
    SGD is the commonly used abbreviation and nickname for the German football club Dynamo Dresden.
  • D. “Large-Scale Machine Learning with Stochastic Gradient Descent” chosen
    “Large-Scale Machine Learning with Stochastic Gradient Descent” is a widely cited work by Léon Bottou that analyzes and advocates stochastic gradient descent as an efficient optimization method for large-scale machine learning problems.
  • E. AdaGrad
    AdaGrad is an adaptive gradient descent optimization algorithm that adjusts learning rates for individual parameters based on their historical gradients, often improving convergence in sparse settings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0414877d88190804ee76566004e13 completed April 16, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d5e82a48190bb0a10ebc2412129 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 4:06 a.m.