Probabilistic language models for identifying sequential reading order of discontinuous text segments

A computing system comprising:

• one or more hardware processors and memory configured to provide computer program instructions to the one or more hardware processors;
• a means for identifying a sequential reading order for a plurality of discontinuous text segments associated with a document, using a probabilistic language model that comprises an n-gram model or a recurrent neural network trained on ground truth reading-order sequences and is configured to use the one or more hardware processors to predict a score, for each pair of text segments of the plurality of discontinuous text segments, indicating a likelihood that the pair of text segments is in a correct reading-order sequence;
• a re-sequencing module configured to use the one or more hardware processors to:
• determine ordered textual content by re-sequencing the plurality of discontinuous text segments in the sequential reading order;
• and
• provide, to a user interface, an indication of the ordered textual content.