A three layer back propagation neural net is set up to study the functional dependency between the semantic class of a bisyllabic Chinese word and that of its two constituent Chinese characters. Simulations were performed using a three-layer back-propagation neural net with various combination of inputs. The inputs are (1) semantic classes of the constituent characters, (2) Entropy of the characters and (3) semantic strength! 1 ] of the characters. Our simulations show that we can obtain the meaning class of a bisyllabic word from the meaning classes of its two constituent characters to an accuracy of 81% by taking the semantic classes and semantic strength of the characters as input. This research establishes the dependency between the meaning class of a Chinese compound word and that of its two constituent characters.