Triple
T12821563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milestone A |
E306541
|
entity |
| Predicate | regulatoryFramework |
P1051
|
FINISHED |
| Object |
Adaptive Acquisition Framework
The Adaptive Acquisition Framework is the U.S. Department of Defense’s modern, flexible system of acquisition pathways and policies designed to streamline how defense capabilities are developed, procured, and fielded.
|
E1004068
|
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: Adaptive Acquisition Framework | Statement: [Milestone A, regulatoryFramework, Adaptive Acquisition Framework]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adaptive Acquisition Framework Context triple: [Milestone A, regulatoryFramework, Adaptive Acquisition Framework]
-
A.
Soft Capture and Rendezvous System
The Soft Capture and Rendezvous System is a NASA-developed docking interface designed to enable future spacecraft to safely rendezvous with, capture, and potentially service or deorbit satellites such as the Hubble Space Telescope.
-
B.
Innovations approach to detection and estimation
"Innovations approach to detection and estimation" is a seminal work by Thomas Kailath that develops a powerful stochastic framework for solving signal detection and parameter estimation problems, particularly in control and communication systems.
-
C.
Adept AI
Adept AI is an artificial intelligence research and product company focused on building AI agents that can use existing software tools to perform complex tasks for users.
-
D.
Åström–Wittenmark adaptive control framework
The Åström–Wittenmark adaptive control framework is a foundational methodology in control theory that systematically designs controllers capable of adjusting their parameters in real time to handle unknown or time-varying system dynamics.
-
E.
Adaptation Framework
The Adaptation Framework is an international policy framework under the UN climate regime that guides and coordinates global efforts to adapt to the impacts of climate change, particularly in vulnerable developing countries.
- 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: Adaptive Acquisition Framework Triple: [Milestone A, regulatoryFramework, Adaptive Acquisition Framework]
Generated description
The Adaptive Acquisition Framework is the U.S. Department of Defense’s modern, flexible system of acquisition pathways and policies designed to streamline how defense capabilities are developed, procured, and fielded.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Adaptive Acquisition Framework Target entity description: The Adaptive Acquisition Framework is the U.S. Department of Defense’s modern, flexible system of acquisition pathways and policies designed to streamline how defense capabilities are developed, procured, and fielded.
-
A.
Soft Capture and Rendezvous System
The Soft Capture and Rendezvous System is a NASA-developed docking interface designed to enable future spacecraft to safely rendezvous with, capture, and potentially service or deorbit satellites such as the Hubble Space Telescope.
-
B.
Innovations approach to detection and estimation
"Innovations approach to detection and estimation" is a seminal work by Thomas Kailath that develops a powerful stochastic framework for solving signal detection and parameter estimation problems, particularly in control and communication systems.
-
C.
Adept AI
Adept AI is an artificial intelligence research and product company focused on building AI agents that can use existing software tools to perform complex tasks for users.
-
D.
Åström–Wittenmark adaptive control framework
The Åström–Wittenmark adaptive control framework is a foundational methodology in control theory that systematically designs controllers capable of adjusting their parameters in real time to handle unknown or time-varying system dynamics.
-
E.
Adaptation Framework
The Adaptation Framework is an international policy framework under the UN climate regime that guides and coordinates global efforts to adapt to the impacts of climate change, particularly in vulnerable developing countries.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9fcc8c8190a926ab0481d28f14 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ed165188190a4cac781c753fb23 |
completed | May 2, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69f68f8d2ca08190a385635fb6130a9f |
completed | May 2, 2026, 11:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69033a66481908bf4ae23fced5983 |
completed | May 3, 2026, midnight |
Created at: April 9, 2026, 5:32 p.m.