You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: Knowledge-enhanced pre-training.Following previous studies (Nogueiraet al., 2019a; Yanet al., 2021; Kim and Ko, 2021), we conduct continual pre-training on MSMARCO corpus to warm up the parameters of GMN module.We apply Masked Language Model (MLM) (Devlinet al., 2018) and Sentence Relation Prediction (SRP) (Wang et al., 2019) as the pre-training tasks in KERM.Compared to conventional Next Sentence Prediction (NSP) (Devlinet al., 2018), the task of SRP is to predict whether a given sentence is the next sentence, previous sentence relation or no relation with another sentence. To incorporate knowledge during the pre-training stage, we construct a meta-graph for each sentence pair, and apply the knowledge aggregation process as introduced above.The pre-training loss is defined as\mathcal{L}_{p}=\mathcal{L}_{MLM}+\mathcal{L}_{SRP}.

Question: How is next sentence prediction (NSP) different from sentence relation prediction (SRP)?
Compared to conventional Next Sentence Prediction (NSP), Sentence Relation Prediction (SRP) aims to predict whether a given sentence is the next sentence, previous sentence relation, or no relation with another sentence.