Triple
T7937429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM Data and AI portfolio |
E184318
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
IBM Watson Studio
IBM Watson Studio is a cloud-based data science and machine learning platform that enables users to build, train, and deploy AI models collaboratively at scale.
|
E699600
|
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: IBM Watson Studio | Statement: [IBM Data and AI portfolio, hasComponent, IBM Watson Studio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IBM Watson Studio Context triple: [IBM Data and AI portfolio, hasComponent, IBM Watson Studio]
-
A.
IBM Watson
IBM Watson is IBM’s artificial intelligence platform known for its natural language processing, machine learning capabilities, and high-profile applications such as winning on Jeopardy! and powering enterprise AI solutions.
-
B.
IBM Watson Discovery
IBM Watson Discovery is an AI-powered enterprise search and text analytics platform that uses natural language processing to extract insights from large volumes of unstructured data.
-
C.
Amazon SageMaker
Amazon SageMaker is a fully managed cloud service that enables developers and data scientists to build, train, and deploy machine learning models at scale.
-
D.
Azure Machine Learning
Azure Machine Learning is a cloud-based service from Microsoft for building, training, deploying, and managing machine learning models at scale on Azure.
-
E.
Landing AI
Landing AI is a technology company focused on making artificial intelligence accessible to traditional industries by helping them build and deploy practical AI solutions, particularly in manufacturing and computer vision.
- 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: IBM Watson Studio Triple: [IBM Data and AI portfolio, hasComponent, IBM Watson Studio]
Generated description
IBM Watson Studio is a cloud-based data science and machine learning platform that enables users to build, train, and deploy AI models collaboratively at scale.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: IBM Watson Studio Target entity description: IBM Watson Studio is a cloud-based data science and machine learning platform that enables users to build, train, and deploy AI models collaboratively at scale.
-
A.
IBM Watson
chosen
IBM Watson is IBM’s artificial intelligence platform known for its natural language processing, machine learning capabilities, and high-profile applications such as winning on Jeopardy! and powering enterprise AI solutions.
-
B.
IBM Watson Discovery
IBM Watson Discovery is an AI-powered enterprise search and text analytics platform that uses natural language processing to extract insights from large volumes of unstructured data.
-
C.
Amazon SageMaker
Amazon SageMaker is a fully managed cloud service that enables developers and data scientists to build, train, and deploy machine learning models at scale.
-
D.
Azure Machine Learning
Azure Machine Learning is a cloud-based service from Microsoft for building, training, deploying, and managing machine learning models at scale on Azure.
-
E.
Landing AI
Landing AI is a technology company focused on making artificial intelligence accessible to traditional industries by helping them build and deploy practical AI solutions, particularly in manufacturing and computer vision.
- F. None of above.
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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aef2394819086eea1f6ab117aed |
completed | March 31, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc564a4fac8190972f9dfa7c026ea8 |
completed | March 31, 2026, 11:18 p.m. |
| NEDg | Description generation | batch_69cc5822581481908a143376bee599ec |
completed | March 31, 2026, 11:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc58f549388190ba6c8b41c0820cd6 |
completed | March 31, 2026, 11:29 p.m. |
Created at: March 30, 2026, 5:08 p.m.