Most current methods adopt a statistical framework, without full semantic analysis of the selected content passages; this makes the comparison of content across multiple selected text passages hard, and necessarily approximated by the textual similarity of those passages.
most current summarization or longanswer question-answering systems employ two levels of analysis: a content level, where every textual unit is scored according to the concepts or features it covers, and a textual level, when, before being added to the final output, the textual units deemed to be important are compared to each other and only those that are not too similar to other candidates are included in the final answer or summary.