This paper discusses problems of right retrievals of memory, preferential orderings, and script selection/withdrawal in natural language processing (NLP). Atmosphere is introduced to solve these problems. It works as a contextual indicator which roughly grasps what is being talked about. An implementation mechanism for atmosphere is presented inspired by artificial neural network researches. It is characterized by microfeature representation, a chronological FIFO (First-In First- Out memory), and threshold-based selection. The mechanism constructs an intuition module and works for N L P while cooperating with a logic module which uses T M S to check the justifications of preferential decisions done by the intuition module.

Read users' queries to databases written in their natural language tend to be extra-grammatical, erroneous and, sometimes just a sequence of keywords. Since most conventional natural language interfaces are seminatural, they cannot treat such real queries very well. This paper proposes a new natural language query interpretation model, named SIMPLA. Because the model has a keyword-based parsing mechanism, it is very robust to cope with extragrammatical sentences. The strong keyword-based parsing capability is very dependent upon its target database's being a "card''-type. SIMPLA provides several operators to define peripheral knowledge, regarding the target database. Such peripheral knowledge is stored virtually in parts of the target ''card"-type database. Since the target database with the peripheral knowledge remains •'card"-type, S I M P L A does not decrease its robust natural language processing capability, while it embodies the ability to respond to questions concerning peripheral questions.