Action Representation for Natural Language Interfaces to Agent Systems
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we outline a framework for the development of natural language interfaces to agent systems, with a focus on action representation. The architecture comprises a natural language parser and case frame based analysis for semantic representation for the linguistic content of the input. The knowledge base, used as core instance of the mapping and interpretation process, features a representation of actions and related objects in a conceptual hierarchy, which is suited to provide a connection to the artificial agent?s repertoire of actions. The framework thus features representations of actions, specifically designed to link linguistic inputs of the human user to the action set of an artificial agent. The framework has been employed in the development of various agent systems and their natural language interfaces, including simulated household robots, an interior design system, a travel planner, a cook, and a remote controlled toy car..
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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