  Mention detection is an important component of coreference resolution system,
where mentions such as name, nominal, and pronominals are identified. These
mentions can be purely coreferential mentions or singleton mentions
(non-coreferential mentions). Coreferential mentions are those mentions in a
text that refer to the same entities in a real world. Whereas, singleton
mentions are mentioned only once in the text and do not participate in the
coreference as they are not mentioned again in the following text. Filtering of
these singleton mentions can substantially improve the performance of a
coreference resolution process. This paper proposes a singleton mention
detection module based on a fully connected network and a Convolutional neural
network for Hindi text. This model utilizes a few hand-crafted features and
context information, and word embedding for words. The coreference annotated
Hindi dataset comprising of 3.6K sentences, and 78K tokens are used for the
task. In terms of Precision, Recall, and F-measure, the experimental findings
obtained are excellent.
