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	title        = {Detecting Context Dependence in Exercise Item Candidates Selected from Corpora},
	abstract     = {We explore the factors influencing the dependence of single sentences on their larger textual context in order to automatically identify
candidate sentences for language learning exercises from corpora which are presentable in
isolation. An in-depth investigation of this
question has not been previously carried out.
Understanding this aspect can contribute to a
more efficient selection of candidate sentences
which, besides reducing the time required for
item writing, can also ensure a higher degree
of variability and authenticity. We present a
set of relevant aspects collected based on the
qualitative analysis of a smaller set of context-dependent corpus example sentences. Furthermore, we implemented a rule-based algorithm using these criteria which achieved
an average precision of 0.76 for the identification
of different issues related to context dependence. The method has also been
evaluated empirically where 80% of the sentences in which our system did not detect
context-dependent elements were also considered context-independent by human raters.},
	booktitle    = {Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications, June 12 to June 17, 2016, San Diego, USA},
	author       = {Pilán, Ildikó},
	year         = {2016},