Triple
T18705015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transform |
E457346
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | tfx.Transform |
—
|
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: tfx.Transform | Statement: [Transform, abbreviation, tfx.Transform]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: tfx.Transform Context triple: [Transform, abbreviation, tfx.Transform]
-
A.
TensorFlow Transform
chosen
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.
-
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 Extended
TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
-
D.
Kubeflow Pipelines
Kubeflow Pipelines is a platform for building, deploying, and managing end-to-end machine learning workflows on Kubernetes using containerized components.
-
E.
TensorFlow Estimators
TensorFlow Estimators are a high-level TensorFlow API that simplifies building, training, and deploying machine learning models with standardized workflows and production-ready features.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671665bc8190b9b4a4ce4ec5b2eb |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 10, 2026, 11:49 a.m.