Triple
T9838324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deeplearning.ai |
E239157
|
entity |
| Predicate | hasNotableCourse |
P64158
|
FINISHED |
| Object |
TensorFlow in Practice Specialization
TensorFlow in Practice Specialization is an online deep learning program on Coursera that teaches practical TensorFlow skills for building and deploying neural network models.
|
E824069
|
NE FINISHED |
How this triple was built (4 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: TensorFlow in Practice Specialization | Statement: [Deeplearning.ai, hasNotableCourse, TensorFlow in Practice Specialization]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TensorFlow in Practice Specialization Context triple: [Deeplearning.ai, hasNotableCourse, TensorFlow in Practice Specialization]
-
A.
Deeplearning.ai
Deeplearning.ai is an online education company specializing in artificial intelligence and deep learning courses and resources.
-
B.
TensorFlow
TensorFlow is an open-source, end-to-end machine learning and deep learning framework widely used for building, training, and deploying neural network models at scale.
-
C.
TensorFlow ecosystem
The TensorFlow ecosystem is a comprehensive suite of tools, libraries, and extensions built around the TensorFlow machine learning framework to support model development, training, deployment, and visualization.
-
D.
TensorFlow Extended
TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
-
E.
"Deep Learning with Python"
"Deep Learning with Python" is a practical book that introduces deep learning concepts and techniques using the Keras library and the Python ecosystem, aimed at helping developers and researchers build and understand modern neural networks.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TensorFlow in Practice Specialization Triple: [Deeplearning.ai, hasNotableCourse, TensorFlow in Practice Specialization]
Generated description
TensorFlow in Practice Specialization is an online deep learning program on Coursera that teaches practical TensorFlow skills for building and deploying neural network models.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TensorFlow in Practice Specialization Target entity description: TensorFlow in Practice Specialization is an online deep learning program on Coursera that teaches practical TensorFlow skills for building and deploying neural network models.
-
A.
Deeplearning.ai
Deeplearning.ai is an online education company specializing in artificial intelligence and deep learning courses and resources.
-
B.
TensorFlow
TensorFlow is an open-source, end-to-end machine learning and deep learning framework widely used for building, training, and deploying neural network models at scale.
-
C.
TensorFlow ecosystem
The TensorFlow ecosystem is a comprehensive suite of tools, libraries, and extensions built around the TensorFlow machine learning framework to support model development, training, deployment, and visualization.
-
D.
TensorFlow Extended
TensorFlow Extended (TFX) is an end-to-end platform for deploying, managing, and scaling production machine learning pipelines built on TensorFlow.
-
E.
"Deep Learning with Python"
"Deep Learning with Python" is a practical book that introduces deep learning concepts and techniques using the Keras library and the Python ecosystem, aimed at helping developers and researchers build and understand modern neural networks.
- F. None of above. chosen
Provenance (5 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb34921b881909836ba0f5b42a27b |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5d145ac8190ad10a4328216ef54 |
completed | April 5, 2026, 3:24 a.m. |
| NEDg | Description generation | batch_69d1d6bb23cc81909efbeccf147018e8 |
completed | April 5, 2026, 3:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d726e58c819090135d1ff275d2d8 |
completed | April 5, 2026, 3:29 a.m. |
Created at: March 30, 2026, 8:33 p.m.