The teachable language comprehender: a simulation program and theory of language

Abstract

The Teachable Language Comprehender (TLC) is a program designed to be capable of being taught to “comprehend” English text. When text which the program has not seen before is input to it, it comprehends that text by correctly relating each (explicit or implicit) assertion of the new text to a large memory. This memory is a “semantic network” representing factual assertions about the world.

The program also creates copies of the parts of its memory which have been found to relate to the new text, adapting and combining these copies to represent the meaning of the new text. By this means, the meaning of all text the program successfully comprehends is encoded into the same format as that of the memory. In this form it can be added into the memory.

Both factual assertions for the memory and the capabilities for correctly relating text to the memory's prior content are to be taught to the program as they are needed. TLC presently contains a relatively small number of examples of such assertions and capabilities, but within the system, notations for expressing either of these are provided. Thus the program now corresponds to a general process for comprehending language, and it provides a methodology for adding the additional information this process requires to actually comprehend text of any particular kind.

The memory structure and comprehension process of TLC allow new factual assertions and capabilities for relating text to such stored assertions to generalize automatically. That is, once such an assertion or capability is put into the system, it becomes available to help comprehend a great many other sentences in the future. Thus the addition of a single factual assertion or linguistic capability will often provide a large increment in TLC's effective knowledge of the world and in its overall ability to comprehend text.

The program's strategy is presented as a general theory of

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Index Terms

• Applied computing

  • Arts and humanities

    • Language translation

• Computing methodologies

  • Artificial intelligence

    • Natural language processing

  • Modeling and simulation

    • Model development and analysis

      • Model verification and validation