  The automatic extraction of structure from text can be difficult for
machines. Yet, the elicitation of this information can provide many benefits
and opportunities for various applications. Benefits have also been identified
for the area of Requirements Engineering. To evaluate what work has been done
and is currently available, the paper at hand provides an integrative review
regarding Natural Language Processing (NLP) tools for Requirements Engineering.
This assessment was conducted to provide a foundation for future work as well
as deduce insights from the stats quo. To conduct the review, the history of
Requirements Engineering and NLP are described as well as an evaluation of over
136 NLP tools. To assess these tools, a set of criteria was defined. The
results are that currently no open source approach exists that allows for the
direct/primary extraction of information structure and even closed source
solutions show limitations such as supervision or input limitations, which
eliminates the possibility for fully automatic and universal application. As a
results, the authors deduce that the current approaches are not applicable and
a different methodology is necessary. An approach that allows for individual
management of the algorithm, knowledge base, and text corpus is a possibility
being pursued.
