Triple

T17520733
Position Surface form Disambiguated ID Type / Status
Subject LIBSVM E426672 entity
Predicate includesTool P1393 FINISHED
Object svm-scale — NE NERFINISHED

How this triple was built (3 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: svm-scale | Statement: [LIBSVM, includesTool, svm-scale]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: svm-scale
Context triple: [LIBSVM, includesTool, svm-scale]
  • A. libsvm
    libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
  • B. Svm
    Svm is the station code used to identify Svanemøllen railway station in Copenhagen’s public transport system.
  • C. 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.
  • D. 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.
  • E. SVR
    SVR is the set of post-nominal letters used to denote recipients of the Order of the White Rose of Finland.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: svm-scale
Target entity description: svm-scale is a utility program in the LIBSVM suite used to normalize and scale feature values in datasets before training support vector machine models.
  • A. libsvm chosen
    libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
  • B. Svm
    Svm is the station code used to identify Svanemøllen railway station in Copenhagen’s public transport system.
  • C. 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.
  • D. 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.
  • E. SVR
    SVR is the set of post-nominal letters used to denote recipients of the Order of the White Rose of Finland.
  • F. None of above.

Provenance (2 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d23cf08190925510344fa36f57 completed April 19, 2026, 3:58 a.m.
Created at: April 10, 2026, 5:49 a.m.