Triple
T9838325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deeplearning.ai |
E239157
|
entity |
| Predicate | hasNotableCourse |
P64158
|
FINISHED |
| Object | DeepLearning.AI TensorFlow Developer Professional Certificate |
E239157
|
NE FINISHED |
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: DeepLearning.AI TensorFlow Developer Professional Certificate | Statement: [Deeplearning.ai, hasNotableCourse, DeepLearning.AI TensorFlow Developer Professional Certificate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DeepLearning.AI TensorFlow Developer Professional Certificate Context triple: [Deeplearning.ai, hasNotableCourse, DeepLearning.AI TensorFlow Developer Professional Certificate]
-
A.
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.
-
B.
Deeplearning.ai
chosen
Deeplearning.ai is an online education company specializing in artificial intelligence and deep learning courses and resources.
-
C.
"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.
-
D.
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.
-
E.
TensorFlow.js
TensorFlow.js is a JavaScript library that enables training and running machine learning models directly in the browser and in Node.js using TensorFlow.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d1e429682c8190a94339b96d4081f6 |
completed | April 5, 2026, 4:25 a.m. |
Created at: March 30, 2026, 8:33 p.m.