Triple

T4277037
Position Surface form Disambiguated ID Type / Status
Subject GridSearchCV E97067 entity
Predicate inheritsFrom P3800 FINISHED
Object BaseSearchCV
BaseSearchCV is a scikit-learn base class that implements the core logic for hyperparameter search estimators, providing shared functionality for classes like GridSearchCV and RandomizedSearchCV.
 E426667 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: BaseSearchCV | Statement: [GridSearchCV, inheritsFrom, BaseSearchCV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BaseSearchCV
Context triple: [GridSearchCV, inheritsFrom, BaseSearchCV]
  • A. GridSearchCV
    GridSearchCV is a scikit-learn tool that systematically searches over specified hyperparameter values using cross-validation to find the best-performing model configuration.
  • B. RandomizedSearchCV
    RandomizedSearchCV is a scikit-learn tool that performs hyperparameter optimization by randomly sampling parameter combinations and evaluating them via cross-validation.
  • C. Neural Architecture Search
    Neural Architecture Search is an automated machine learning technique that uses algorithms to design and optimize neural network architectures without extensive human intervention.
  • 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. 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.
  • 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: BaseSearchCV
Triple: [GridSearchCV, inheritsFrom, BaseSearchCV]
Generated description
BaseSearchCV is a scikit-learn base class that implements the core logic for hyperparameter search estimators, providing shared functionality for classes like GridSearchCV and RandomizedSearchCV.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BaseSearchCV
Target entity description: BaseSearchCV is a scikit-learn base class that implements the core logic for hyperparameter search estimators, providing shared functionality for classes like GridSearchCV and RandomizedSearchCV.
  • A. GridSearchCV
    GridSearchCV is a scikit-learn tool that systematically searches over specified hyperparameter values using cross-validation to find the best-performing model configuration.
  • B. RandomizedSearchCV
    RandomizedSearchCV is a scikit-learn tool that performs hyperparameter optimization by randomly sampling parameter combinations and evaluating them via cross-validation.
  • C. Neural Architecture Search
    Neural Architecture Search is an automated machine learning technique that uses algorithms to design and optimize neural network architectures without extensive human intervention.
  • 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. 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.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501ef1388190b0c968b069014a59 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b3b52c8190ae7c05448faf5558 completed March 14, 2026, 7:32 p.m.
NEDg Description generation batch_69b5b95083088190b0c993fa2fbc954c completed March 14, 2026, 7:38 p.m.
NED2 Entity disambiguation (via description) batch_69b5b9b8afcc8190822cfd560d064590 completed March 14, 2026, 7:40 p.m.
Created at: March 12, 2026, 11:07 p.m.