Triple

T4599949
Position Surface form Disambiguated ID Type / Status
Subject Python scientific stack E100298 entity
Predicate hasComponent P35 FINISHED
Object scikit-learn E17661 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: scikit-learn | Statement: [Python scientific stack, hasComponent, scikit-learn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: scikit-learn
Context triple: [Python scientific stack, hasComponent, scikit-learn]
  • A. scikit-learn chosen
    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.
  • B. libsvm
    libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
  • C. LogisticRegression
    LogisticRegression is a scikit-learn machine learning estimator that models the probability of class membership using a linear decision boundary with logistic (sigmoid) or related link functions.
  • D. Support Vector Machines
    Support Vector Machines are a class of supervised learning algorithms used primarily for classification and regression tasks, which work by finding the optimal separating hyperplane between data classes in a high-dimensional feature space.
  • E. Apache Mahout
    Apache Mahout is an open-source machine learning library designed to build scalable algorithms for clustering, classification, and recommendation on large datasets, often leveraging big data platforms.
  • 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_69bd43cbc014819098b45f435908f88a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5971f448819090f6e76c7d3ffc2d completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa54bb0c819081265a6d159ad790 completed March 21, 2026, 1:54 a.m.
Created at: March 20, 2026, 1:11 p.m.