Triple
T17520635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pipeline (scikit-learn) |
E426670
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | FeatureUnion |
—
|
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: FeatureUnion | Statement: [Pipeline (scikit-learn), relatedTo, FeatureUnion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FeatureUnion Context triple: [Pipeline (scikit-learn), relatedTo, FeatureUnion]
-
A.
ColumnTransformer
ColumnTransformer is a scikit-learn utility that applies different preprocessing or transformation pipelines to specified columns of a dataset within a single unified estimator.
-
B.
Turi Create
Turi Create is an open-source Python library from Apple that simplifies building, training, and deploying machine learning models, especially for use with Apple’s Core ML framework.
-
C.
TensorFlow Transform
TensorFlow Transform is a TensorFlow-based library for performing scalable, full-pass data preprocessing and feature engineering that can be applied consistently in both training and serving.
-
D.
CatBoost
CatBoost is an open-source gradient boosting library developed by Yandex, optimized for handling categorical features and delivering high-performance machine learning models.
-
E.
Create ML
Create ML is Apple's machine learning tool that lets developers easily build and train models directly on macOS using simple, user-friendly interfaces.
- 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: FeatureUnion Target entity description: FeatureUnion is a scikit-learn tool that combines multiple feature extraction or transformation pipelines into a single, parallelized feature space for modeling.
-
A.
ColumnTransformer
ColumnTransformer is a scikit-learn utility that applies different preprocessing or transformation pipelines to specified columns of a dataset within a single unified estimator.
-
B.
Turi Create
Turi Create is an open-source Python library from Apple that simplifies building, training, and deploying machine learning models, especially for use with Apple’s Core ML framework.
-
C.
TensorFlow Transform
TensorFlow Transform is a TensorFlow-based library for performing scalable, full-pass data preprocessing and feature engineering that can be applied consistently in both training and serving.
-
D.
CatBoost
CatBoost is an open-source gradient boosting library developed by Yandex, optimized for handling categorical features and delivering high-performance machine learning models.
-
E.
Create ML
Create ML is Apple's machine learning tool that lets developers easily build and train models directly on macOS using simple, user-friendly interfaces.
- F. None of above. chosen
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.