Interleaving Natural Language Parsing and Generation Through Uniform Processing

We present a new model of natural language processing in which natural lan guage parsing and generation are strongly interleaved tasks Interleaving of parsing and generation is important if we assume that natural language understanding and production are not only performed in isolation but also work together to obtain subsentential interactions in text revision or dialog systems The core of the model is a new uniform agenda driven tabular algorithm called UTA Although uniformly de ned UTA is able to con gure itself dynamically for either parsing or generation because it is fully driven by the structure of the actual input a string for parsing and a semantic expression for generation E cient interleaving of parsing and generation is obtained through item sharing between parsing and generation This novel processing strategy facilitates the automatic exchange of items i e partial results computed in one direction to the other direction as well The advantage of UTA in combination with the item sharing method is that we are able to extend the use of memorization techniques to the case of an inter leaved approach In order to demonstrate UTA s utility for developing high level performance methods we present a new algorithm for incremental self monitoring during natural language production The paper has been acceppted for publication in the Journal Arti cial Intelligence The research underlying this paper was supported by research grants from the German Science Foundation in its Spe cial Collaborative Research Program on Arti cial Intelligence and Knowledge Based Systems SFB project bild and from the German Bundesministerium f ur Bildung Wissenschaft Forschung und Technologie BMB F to the DFKI projects disco FKZ ITW paradice FKZ ITW and paradime FKZ ITW I would like to thank the following people for the fruitful discussions Karin Harbusch Walter Kasper Martin Kay Klaus Netter Gertjan van Noord Vijay Shankar Hans Uszkoreit Harald Trost Wolfgang Wahlster Mats Wir en