Much attention has recently been paid to natural language processing in information storage and retrieval. This paper describes how the application of natural language processing (NLP) techniques can enhance cross-language information retrieval (CLIR). Using a semi-experimental technique, we took Farsi queries to retrieve relevant documents in English. For translating Persian queries, we used a bilingual machinereadable dictionary. NLP techniques such as tokenization, morphological analysis and part of speech tagging were used in pre-and- post translation phases. Results showed that applying NLP techniques yields more effective CLIR performance.