Triple

T148132
Position Surface form Disambiguated ID Type / Status
Subject Python E3372 entity
Predicate machineLearningLibrary P7265 FINISHED
Object scikit-learn
scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.
E17661 NE FINISHED

How this triple was built (5 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: scikit-learn | Statement: [Python, machineLearningLibrary, scikit-learn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: scikit-learn
Context triple: [Python, machineLearningLibrary, scikit-learn]
  • A. Lifelong Learning Machines program
    The Lifelong Learning Machines program is a DARPA research initiative aimed at developing AI systems that can continuously learn and adapt from experience in dynamic, real-world environments.
  • B. Machine Learning Department, Carnegie Mellon University
    The Machine Learning Department at Carnegie Mellon University is a pioneering academic unit dedicated to research and education in machine learning, artificial intelligence, and related computational disciplines.
  • C. Boltzmann machines
    Boltzmann machines are stochastic recurrent neural networks used for learning complex probability distributions, foundational in unsupervised learning and energy-based models.
  • D. ROC
    ROC is the commonly used abbreviation for the Royal Observer Corps, a former British civil defense organization that monitored aircraft and nuclear explosions during the 20th century.
  • E. Open Data Lab
    Open Data Lab is a World Wide Web Foundation initiative that supports the use of open data to drive social impact, innovation, and better governance, particularly in developing countries.
  • 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: scikit-learn
Triple: [Python, machineLearningLibrary, scikit-learn]
Generated description
scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: scikit-learn
Target entity description: scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.
  • A. Lifelong Learning Machines program
    The Lifelong Learning Machines program is a DARPA research initiative aimed at developing AI systems that can continuously learn and adapt from experience in dynamic, real-world environments.
  • B. Machine Learning Department, Carnegie Mellon University
    The Machine Learning Department at Carnegie Mellon University is a pioneering academic unit dedicated to research and education in machine learning, artificial intelligence, and related computational disciplines.
  • C. Boltzmann machines
    Boltzmann machines are stochastic recurrent neural networks used for learning complex probability distributions, foundational in unsupervised learning and energy-based models.
  • D. ROC
    ROC is the commonly used abbreviation for the Royal Observer Corps, a former British civil defense organization that monitored aircraft and nuclear explosions during the 20th century.
  • E. Open Data Lab
    Open Data Lab is a World Wide Web Foundation initiative that supports the use of open data to drive social impact, innovation, and better governance, particularly in developing countries.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: machineLearningLibrary
Context triple: [Python, machineLearningLibrary, scikit-learn]
  • A. model
    Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
  • B. isMainLibraryOf
    Indicates that a library serves as the primary or central library for a given organization, system, or collection.
  • C. programmingLanguage
    Indicates that one entity is a programming language used to create, control, or interact with the other entity.
  • D. commonlyImplementedBy
    Indicates that the referenced item (e.g., a standard, interface, or pattern) is frequently realized or put into practice by the associated implementing entities.
  • E. computes
    Indicates that one entity performs a calculation or processing operation to produce a result from given data or inputs.
  • F. None of above. chosen

Provenance (7 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_69a252868de4819080e21c9938bfe8b6 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a258808ff08190a06b6206f635612b completed Feb. 28, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2c27754a881908ef5a96e05e515e3 completed Feb. 28, 2026, 10:24 a.m.
NEDg Description generation batch_69a2c37177348190857d52872e6ab393 completed Feb. 28, 2026, 10:29 a.m.
NED2 Entity disambiguation (via description) batch_69a2c3c512f08190bb87f874524b1616 completed Feb. 28, 2026, 10:30 a.m.
PD Predicate disambiguation batch_69a256580c2c8190beecca60ca8595f3 completed Feb. 28, 2026, 2:43 a.m.
PDg Predicate description generation batch_69a2587e598c81909e1082b813971f48 completed Feb. 28, 2026, 2:52 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.