An architectural framework for natural language interfaces to agent systems.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Christel Kemke University of Manitoba Winnipeg, MB, R3T 2N2 Canada ckemke@cs.umanitoba.ca ABSTRACT In this paper, we describe an architectural framework for the development of natural language interfaces to agent systems. Since the communication between human and artificial agents is mostly task-related, the focus of the suggested architecture is on action representations as core structure and thread in the overall processing. The architectural framework we suggest is based on various forms of action representations and consists of a sequence of transformations, which converts the user’s verbal input into a suitable set of agent actions to produce a response to the input. This process reduces stepwise the complexity and ambiguity of the natural language input by using pre-defined sets of interim actions at different levels, and thus increases the robustness and reliability of the natural language interface. The architecture was employed in the design of several natural language interfaces to agent systems. KEY WORDS Natural Language Interfaces, Human-Agent Communication, Human-Machine Interaction, Knowledge Representation, Ontology, Agent Systems, Action Theory, Description Logic
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it