Text mining aims to understand texts correctly by utilising several phases to collect those features of Arabic words which are valuable and important to the applications mentioned above in making a correct decision. The technology then builds a strong system that relies on AI techniques, such as neural networks, to collect words in accordance with those features. An ANN is a collection of connected nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron is one that receives a signal then processes it and can signal to neurons connected to it. The current study is concerned with building a system for analysing words in the Arabic language. This system can be included in any application to address the Arabic language, becoming part of it. The system generates strings for all names and pronouns appearing in the entered text and depends mainly on the automatic assembly of a set features by using neural networks. We implemented the system, with its two phases, on the documents in succession. The results were encouraging, ranging between 83% and 96%.