FrameNet Grounded in 4D+T via Tripix

Technical Architecture Proposal FrameNet Grounded in 4D+T via Tripix (https://zenodo.org/records/15717565) Need to Ask permission and cooperation to Berkeley FrameNet:https://framenet.icsi.berkeley.edu/ 1. Objective of the System Build a computational infrastructure that: ✅ Dynamically generates conceptual Frames grounded on real or simulated perceptions. ✅ Associates events perceived in 4D+T space to semantically formalized frames. ✅ Creates a situated computational lexicon, interoperable with traditional FrameNet. ✅ Enables inferences, linguistic parsing and verbal production based on embodied experience. 2. Main Modules Schema +--------------------------+| Modulo Tripix Core | --> Agente embodied, percezione, mappa 4D+T+--------------------------+ | v+--------------------------+| Modulo Event Abstraction | --> Identificazione e classificazione eventi percepiti+--------------------------+ | v+--------------------------+| Modulo Frame Generator | --> Costruzione dinamica di Frame grounded+--------------------------+ | v+--------------------------+| Modulo Lessico Situato | --> Creazione lessico, ruoli semantici, allineamento con FrameNet+--------------------------+ | v+--------------------------+| Modulo Linguaggio & Reasoning | --> Comprensione e produzione linguistica, inferenze+--------------------------+ 3. Technical Detail of Components A.Tripix Core Implementation of virtual or physical agents: 3D+T physics simulators: Unreal Engine, Unity, MuJoCo. Real sensorimotor input for robot (optional advanced stage). 4D+T data structure: Explicit representation of objects, trajectories, actions, spatial/temporal relations. Event mapping according to Tripix specifications ( see Usai, 2025 ). B. Event Abstraction Module Perceptual pattern recognition: Computer vision, motion tracking, object and agent recognition. Event formalization: Definition of atomic events (e.g. taking object , moving towards ) and complex events (e.g. trading , social interaction ). Output: Structured flow of events annotated in 4D+T space. C. Frame Generator Frame extraction algorithm: Recurrent analysis of event configurations. Automatic induction of conceptual frames with semantic roles. Example: Eventi ricorrenti: [Agente_A si avvicina, Agente_B consegna oggetto, Agente_A si allontana] --> Frame: Commerce_Transaction_4DT Roles: Venditore, Compratore, Oggetto, Luogo, Tempo FrameNet Integration: Mapping emerging frames onto existing frames. Dynamic extension of the FrameNet repertoire with grounded variants. D. Situated Lexicon Association between grounded frames and linguistic expressions: Annotation of linguistic corpora with references to perceived frames. Possible use of LLM with situated fine-tuning (Constraints: only for lexical mapping, avoiding symbolic confusion). Bilingual lexicon creation: Computational version of the frames in natural language (EN/IT initially). Multilingual support in later stages. E. Language and Reasoning Module Situational parsing: Given an instruction or sentence, the agent understands by drawing on the grounded FrameNet. Language production: Description of perceptions and actions using natural language related to experiential frames. Inference: Inferring situational implications from perceived frames. 4. Suggested Technologies Component Technologies 4D+T Simulation Unity, Unreal Engine, MuJoCo, Habitat AI Vision and perception OpenCV, YOLOv8, Segment Anything Model (SAM) Machine Learning PyTorch, TensorFlow Ontologies & Semantics RDF/OWL, FrameNet dataset, Tripix RDF Extensions Natural language spaCy, NLTK, LLM controlled (GPT, LLaMA) for lexical alignment 5. Roadmap Implementation Phases Phase Objective Estimated duration 1. MVP Simulator with Tripix and basic perception 3-6 months 2. Event Abstraction & Frame Generator Extracting the first frames located 6 months 3. Vocabulary & Situated Language Frame-language mapping 6-9 months 4. Advanced Reasoning & Scientific Validation 12 months 6. Possible Future Developments ✅ Extension to real robots for grounding in the physical world. ✅ Integration with specialized languages (medicine, navigation, etc.). ✅ Evolution towards a generalized multi-domain Grounded FrameNet✅ Publications in Cognitive Science , ACL , NeurIPS , AI & Society . ✅ Horizon Europe proposal (Cluster 4, AI Destination and Human-AI Interaction). Creating a Grounded FrameNet in 4D+T , based on the Tripix paradigm, is: ✔ Conceptually solid, anchored in cutting-edge literature. ✔ Technologically feasible with existing tools. ✔ Potentially revolutionary for symbolic-perceptual and situated semantic AI.