• Dr Shahebaz Ahmed Khan
• Dr Mohammed Abdul Qadeer
• Dr Abdul Ahad Afroz

One of the major problems we come across in NLP is processing of discourse structure. To train the NLP models, we make use of discourse analysis. The discourse is full of exceptions, dualities and ambiguities which make the computers to understand remember and learn. Due to the corpus ambiguity it sometimes becomes very difficult to the computers to find the relationship among the various words and predicts the actual results. The coherent group of sentences in the corpus must make a sense and should produce finite quality meanings for the users. The imprecise expressions can be dealt with the concepts of coherence and discourse analysis. To reflect the original and actual meaning even though the proper context is not provided, the discourse analysis helps to train the NLP models to predict the actual meaning that can justify the use of Artificial Intelligence applications. The idea of coherence resolution finds all the ’mentions’ to process natural languages in computer systems effectively with accurate contextual meaning predictions.

Coherence, discourse structure, corpus, imprecise expression, resolution, context etc.

"COHERENCE AND DISCOURSE STRUCTURE ANALYSIS FOR THE AMBIGUOUS CORPUS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 10, page no.g405-g409, October-2023, Available :http://www.jetir.org/papers/JETIR2310548.pdf

"COHERENCE AND DISCOURSE STRUCTURE ANALYSIS FOR THE AMBIGUOUS CORPUS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 10, page no. ppg405-g409, October-2023, Available at : http://www.jetir.org/papers/JETIR2310548.pdf