Triple
T12325591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SCORM |
E293821
|
entity |
| Predicate | developedBy |
P73
|
FINISHED |
| Object |
Advanced Distributed Learning Initiative
The Advanced Distributed Learning Initiative is a U.S. Department of Defense program that develops and promotes standards and technologies to enable interoperable, reusable, and accessible e-learning content and systems.
|
E975154
|
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: Advanced Distributed Learning Initiative | Statement: [SCORM, developedBy, Advanced Distributed Learning Initiative]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Advanced Distributed Learning Initiative Context triple: [SCORM, developedBy, Advanced Distributed Learning Initiative]
-
A.
Lifelong Learning Machines program
The Lifelong Learning Machines program is a DARPA research initiative aimed at developing AI systems that can continuously learn and adapt from experience in dynamic, real-world environments.
-
B.
Large-Scale Distributed Deep Networks
Large-Scale Distributed Deep Networks is a seminal research work that introduced methods for training deep neural networks efficiently across large-scale distributed computing infrastructure, enabling breakthroughs in modern large-scale AI systems.
-
C.
“Large-Scale Machine Learning with Stochastic Gradient Descent”
“Large-Scale Machine Learning with Stochastic Gradient Descent” is a widely cited work by Léon Bottou that analyzes and advocates stochastic gradient descent as an efficient optimization method for large-scale machine learning problems.
-
D.
Data-Driven Discovery Initiative
The Data-Driven Discovery Initiative is a research program that advances scientific discovery by supporting innovative data science methods, tools, and researchers across disciplines.
-
E.
Technology-Enabled Learning initiative
The Technology-Enabled Learning initiative is a Commonwealth of Learning program that supports institutions and educators in effectively integrating digital technologies into teaching and learning to improve access and quality in education.
- 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: Advanced Distributed Learning Initiative Triple: [SCORM, developedBy, Advanced Distributed Learning Initiative]
Generated description
The Advanced Distributed Learning Initiative is a U.S. Department of Defense program that develops and promotes standards and technologies to enable interoperable, reusable, and accessible e-learning content and systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Advanced Distributed Learning Initiative Target entity description: The Advanced Distributed Learning Initiative is a U.S. Department of Defense program that develops and promotes standards and technologies to enable interoperable, reusable, and accessible e-learning content and systems.
-
A.
Lifelong Learning Machines program
The Lifelong Learning Machines program is a DARPA research initiative aimed at developing AI systems that can continuously learn and adapt from experience in dynamic, real-world environments.
-
B.
Large-Scale Distributed Deep Networks
Large-Scale Distributed Deep Networks is a seminal research work that introduced methods for training deep neural networks efficiently across large-scale distributed computing infrastructure, enabling breakthroughs in modern large-scale AI systems.
-
C.
“Large-Scale Machine Learning with Stochastic Gradient Descent”
“Large-Scale Machine Learning with Stochastic Gradient Descent” is a widely cited work by Léon Bottou that analyzes and advocates stochastic gradient descent as an efficient optimization method for large-scale machine learning problems.
-
D.
Data-Driven Discovery Initiative
The Data-Driven Discovery Initiative is a research program that advances scientific discovery by supporting innovative data science methods, tools, and researchers across disciplines.
-
E.
Technology-Enabled Learning initiative
The Technology-Enabled Learning initiative is a Commonwealth of Learning program that supports institutions and educators in effectively integrating digital technologies into teaching and learning to improve access and quality in education.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4e7e588190b37e2413bc649198 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e8d27288190bdf32acd600141db |
completed | May 2, 2026, 3:55 p.m. |
| NEDg | Description generation | batch_69f61f9493d081909a543bcafeb508d1 |
completed | May 2, 2026, 4 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f620ad9ec0819099909142fbad6412 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 8, 2026, 9:53 p.m.