@article{Stede11,
  author = "Manfred Stede",
  title = "The search for robustness in natural language understanding",
  journal = "Artificial intelligence review",
  volume = "6",
  year = "1992",
  pages = "383--414",
  abstract = "<P> Practical natural language understanding systems used to be
              concerned with very small miniature domains only: They knew exactly what
              potential text might be about, and what kind of sentence structures to
              expect.  This optimistic assumption is no longer feasible if NLU is to
              scale up to deal with text that naturally occurs in the ``real world''.  The
              key issue is robustness: The system needs to be prepared for cases where
              the input data does not correspond to the expectations encoded in the
              grammar.  In this paper, we survey the approaches towards the robustness
              problem that have been developed throughout the last decade.  We inspect
              techniques to overcome both syntactically and semantically ill-formed input
              in sentence parsing and then look briefly into more recent ideas concerning
              the extraction of information from texts, and the related question of the
              role that linguistic research plays in this game.  Finally, the robust
              sentence parsing schemes are classified on a more abstract level of
              analysis.</p>"
}