Triple
T7937435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM Data and AI portfolio |
E184318
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
IBM Industry Accelerators for Data and AI
IBM Industry Accelerators for Data and AI are pre-built, industry-specific solution frameworks that help organizations rapidly apply AI and advanced analytics to common business use cases using IBM’s data and AI technologies.
|
E184318
|
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 Industry Accelerators for Data and AI | Statement: [IBM Data and AI portfolio, hasComponent, IBM Industry Accelerators for Data and AI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IBM Industry Accelerators for Data and AI Context triple: [IBM Data and AI portfolio, hasComponent, IBM Industry Accelerators for Data and AI]
-
A.
IBM Data and AI portfolio
The IBM Data and AI portfolio is a comprehensive suite of data management, analytics, and artificial intelligence products and services designed to help organizations collect, organize, and analyze data at scale.
-
B.
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.
-
C.
Adobe Sensei AI platform
Adobe Sensei AI platform is Adobe’s artificial intelligence and machine learning framework that powers intelligent features across its creative and experience products, enabling automated, context-aware tools for tasks like image editing, personalization, and content optimization.
-
D.
Robert Bosch Centre for Data Science and Artificial Intelligence
The Robert Bosch Centre for Data Science and Artificial Intelligence is a leading interdisciplinary research hub focused on advancing AI and data science through cutting-edge research, innovation, and industry collaboration.
-
E.
Einstein AI
Einstein AI is Salesforce’s integrated artificial intelligence platform that powers predictive analytics, automation, and intelligent insights across its CRM ecosystem.
- 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 Industry Accelerators for Data and AI Triple: [IBM Data and AI portfolio, hasComponent, IBM Industry Accelerators for Data and AI]
Generated description
IBM Industry Accelerators for Data and AI are pre-built, industry-specific solution frameworks that help organizations rapidly apply AI and advanced analytics to common business use cases using IBM’s data and AI technologies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: IBM Industry Accelerators for Data and AI Target entity description: IBM Industry Accelerators for Data and AI are pre-built, industry-specific solution frameworks that help organizations rapidly apply AI and advanced analytics to common business use cases using IBM’s data and AI technologies.
-
A.
IBM Data and AI portfolio
chosen
The IBM Data and AI portfolio is a comprehensive suite of data management, analytics, and artificial intelligence products and services designed to help organizations collect, organize, and analyze data at scale.
-
B.
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.
-
C.
Adobe Sensei AI platform
Adobe Sensei AI platform is Adobe’s artificial intelligence and machine learning framework that powers intelligent features across its creative and experience products, enabling automated, context-aware tools for tasks like image editing, personalization, and content optimization.
-
D.
Robert Bosch Centre for Data Science and Artificial Intelligence
The Robert Bosch Centre for Data Science and Artificial Intelligence is a leading interdisciplinary research hub focused on advancing AI and data science through cutting-edge research, innovation, and industry collaboration.
-
E.
Einstein AI
Einstein AI is Salesforce’s integrated artificial intelligence platform that powers predictive analytics, automation, and intelligent insights across its CRM ecosystem.
- 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_69cb5c0a96ac819099ad30fb925eb329 |
completed | March 31, 2026, 5:30 a.m. |
| NEDg | Description generation | batch_69cb7634f4dc8190b5e537f24bccd651 |
completed | March 31, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cbb67e77a48190b93c6ba61becfac4 |
completed | March 31, 2026, 11:56 a.m. |
Created at: March 30, 2026, 5:08 p.m.