With FGREP, distributed representations for words are developed as part of the task. The representations reflect how the words are used in the task, and in this sense, also stand for the meanings of the words: words that are used the same way have similar representations. FGREP representations lead to good generalization and robustness under noise, and the method frees the system designer from having to encode the representations by hand. FGREP is used for example in DISCERN, SPEC, DISLEX, and the semantic disambiguation projects described on this page.