Triple
T18705248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TensorFlow Transform |
E457351
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | tf.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: tf.Transform | Statement: [TensorFlow Transform, shortName, tf.Transform]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: tf.Transform Context triple: [TensorFlow Transform, shortName, tf.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.
Transformations
"Transformations" is an influential art-critical work by British critic Roger Fry that explores the nature and evolution of modern art and aesthetic experience.
-
C.
Transformations
Transformations is a 1971 poetry collection by Anne Sexton that retells and darkly reimagines Grimm fairy tales through a confessional, feminist lens.
-
D.
Transform
Transform is a TensorFlow Extended (TFX) component used for scalable data preprocessing and feature engineering in machine learning pipelines.
-
E.
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.
- 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.