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In the framework of meaning representation in Natural Language Processing (NLP), we aim to develop a system that can be used for heterogeneous applications such as Machine Translation, Information Retrieval or Lexical Access. This system is based on six hypotheses which concern meaning representation and acquisition. In this paper, we discuss the related hypotheses that motivate the construction of a such system and how these hypotheses, together with NLP software engineering concerns, led us to conceive a distributed multi-agent system for our goals. We present Blexisma2, a distributed multi-agent system for NLP, its conceptual properties, and an example of inter-agent collaboration. The system is currently being tested on a Grid computing environment.