We present a novel approach for extracting noun phrases in general and named entities in particular from a digital repository of text documents. The problem of coreference resolution has been divided into two subproblems: pronoun resolution and non-pronominal resolution. A rule based-technique was used for pronoun resolution while a learning approach for non-pronominal resolution. For named entity resolution

disambiguation arises mainly due to polysemy and synonymy. The proposed approach fixes both problems with the help of WordNet and the Word Sense Disambiguation tool. The proposed approach

to our knowledge

outperforms several baseline techniques with a higher balanced

F

-measure

which is harmonic mean of recall and precision. The improvements in the system performance are due to the filtering of antecedents for the anaphor based on several linguistic disagreements

use of a hybrid approach

and increment in the feature vector to include more linguistic details in the learning technique.