Triple
T9838319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deeplearning.ai |
E239157
|
entity |
| Predicate | hasNotableCourse |
P64158
|
FINISHED |
| Object |
Deep Learning Specialization
Deep Learning Specialization is a popular online course series, led by Andrew Ng, that teaches core deep learning concepts and practical neural network techniques through hands-on projects.
|
E239157
|
NE FINISHED |
How this triple was built (5 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: Deep Learning Specialization | Statement: [Deeplearning.ai, hasNotableCourse, Deep Learning Specialization]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deep Learning Specialization Context triple: [Deeplearning.ai, hasNotableCourse, Deep Learning Specialization]
-
A.
Deeplearning.ai
Deeplearning.ai is an online education company specializing in artificial intelligence and deep learning courses and resources.
-
B.
"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.
-
C.
Deep Learning (book)
Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
-
D.
MS in Machine Learning
MS in Machine Learning is a specialized graduate program at Carnegie Mellon University focused on advanced theory and applications of machine learning and statistical methods for building intelligent systems.
-
E.
NVIDIA AI Workflows
NVIDIA AI Workflows are pre-built, end-to-end AI pipelines from NVIDIA that streamline the development, deployment, and scaling of AI applications across common enterprise use cases.
- 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: Deep Learning Specialization Triple: [Deeplearning.ai, hasNotableCourse, Deep Learning Specialization]
Generated description
Deep Learning Specialization is a popular online course series, led by Andrew Ng, that teaches core deep learning concepts and practical neural network techniques through hands-on projects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Deep Learning Specialization Target entity description: Deep Learning Specialization is a popular online course series, led by Andrew Ng, that teaches core deep learning concepts and practical neural network techniques through hands-on projects.
-
A.
Deeplearning.ai
chosen
Deeplearning.ai is an online education company specializing in artificial intelligence and deep learning courses and resources.
-
B.
"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.
-
C.
Deep Learning (book)
Deep Learning (book) is a foundational textbook that systematically introduces the theory and practice of modern deep neural networks, co-authored by leading researchers including Yoshua Bengio.
-
D.
MS in Machine Learning
MS in Machine Learning is a specialized graduate program at Carnegie Mellon University focused on advanced theory and applications of machine learning and statistical methods for building intelligent systems.
-
E.
NVIDIA AI Workflows
NVIDIA AI Workflows are pre-built, end-to-end AI pipelines from NVIDIA that streamline the development, deployment, and scaling of AI applications across common enterprise use cases.
- F. None of above.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableCourse Context triple: [Deeplearning.ai, hasNotableCourse, Deep Learning Specialization]
-
A.
notableCourse
chosen
Indicates that a course is particularly significant, distinguished, or noteworthy in relation to an entity (such as a person or institution).
-
B.
notableCourseType
Indicates that a course has a particular notable or distinguished type or classification (e.g., flagship, honors, or otherwise specially recognized).
-
C.
hasPrimaryCourse
Indicates that an entity is associated with its main or principal course in a given context (such as a meal, curriculum, or sequence of offerings).
-
D.
hasMultipleCourses
Indicates that an entity is associated with more than one course within the given context.
-
E.
taughtCourse
Indicates that an entity (typically an instructor) has taught a particular course.
- F. None of above.
Provenance (6 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. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:33 p.m.