Triple
T17520636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pipeline (scikit-learn) |
E426670
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | ColumnTransformer |
—
|
NE NERFINISHED |
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: ColumnTransformer | Statement: [Pipeline (scikit-learn), relatedTo, ColumnTransformer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ColumnTransformer Context triple: [Pipeline (scikit-learn), relatedTo, ColumnTransformer]
-
A.
ColumnTransformer
chosen
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.
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.
-
C.
TransformStream
TransformStream is a web streams API interface that enables transforming data chunks passing through a readable–writable stream pair, such as for compression, encryption, or format conversion in streaming workflows.
-
D.
Transformer
Transformer is a neural network architecture based on self-attention mechanisms that has become the foundation for modern large language models and many state-of-the-art systems in natural language processing.
-
E.
Box–Cox transformation
The Box–Cox transformation is a family of power transformations used in statistics to stabilize variance and make data more normally distributed for modeling and analysis.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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.