Triple
T18704834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ExampleGen |
E457342
|
entity |
| Predicate | supportsFormat |
P203
|
FINISHED |
| Object | TFRecord |
—
|
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: TFRecord | Statement: [ExampleGen, supportsFormat, TFRecord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TFRecord Context triple: [ExampleGen, supportsFormat, TFRecord]
-
A.
tf.data API
The tf.data API is a TensorFlow library for building efficient, scalable input pipelines that load, preprocess, and feed data into machine learning models.
-
B.
TensorFlow I/O
TensorFlow I/O is an extension library for TensorFlow that provides specialized input/output operations and dataset integrations for a wide range of file formats and data sources beyond the core framework’s built-in support.
-
C.
Tensor2Tensor library
Tensor2Tensor library is an open-source deep learning toolkit from Google designed to simplify training and sharing state-of-the-art neural network models, particularly for sequence-to-sequence tasks like machine translation.
-
D.
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.
-
E.
TensorFlow Datasets
TensorFlow Datasets is a collection of ready-to-use, standardized datasets for machine learning and deep learning workflows in TensorFlow and other frameworks.
- 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: TFRecord Target entity description: TFRecord is TensorFlow’s native binary file format designed for efficient storage and streaming of large-scale structured data, especially for machine learning pipelines.
-
A.
tf.data API
The tf.data API is a TensorFlow library for building efficient, scalable input pipelines that load, preprocess, and feed data into machine learning models.
-
B.
TensorFlow I/O
TensorFlow I/O is an extension library for TensorFlow that provides specialized input/output operations and dataset integrations for a wide range of file formats and data sources beyond the core framework’s built-in support.
-
C.
Tensor2Tensor library
Tensor2Tensor library is an open-source deep learning toolkit from Google designed to simplify training and sharing state-of-the-art neural network models, particularly for sequence-to-sequence tasks like machine translation.
-
D.
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.
-
E.
TensorFlow Datasets
TensorFlow Datasets is a collection of ready-to-use, standardized datasets for machine learning and deep learning workflows in TensorFlow and other frameworks.
- 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_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.