We describe a method for identifying and performing functional analysis of structured regions that are embedded in natural language documents, such as tables or key-value lists. Such regions often encode information according to ad hoc schemas and avail themselves of visual cues in place of natural language grammar, presenting problems for standard information extraction algorithms. Unlike previous work in table extraction, which assumes a relatively noiseless two-dimensional layout, our aim is to accommodate a wide variety of naturally occurring structure types. Our approach has three main parts. First, we collect and annotate a a diverse sample of “naturally” occurring structures from several sources. Second, we use probabilistic text segmentation techniques, featurized by skip bigrams over spatial and token category cues, to automatically identify contiguous regions of structured text that share a common schema. Finally, we identify the records and fields within each structured region using a combination of distributional similarity and sequence alignment methods, guided by minimal supervision in the form of a single annotated record. We evaluate the last two components individually, and conclude with a discussion of further work.

We present NOMOS, an open-source software framework for annotation, processing, and analysis of multimodal corpora. NOMOS is designed for use by annotators, corpus developers, and corpus consumers, emphasizing configurability for a variety of specific annotation tasks. Its features include synchronized multi-channel audio and video playback, compatibility with several corpora, platform independence, and mixed display of capabilities and a well-defined method for layering datasets. Second, we describe how the system is used. For corpus development and annotation we present a typical use scenario involving the creation of a schema and specialization of the user interface. For processing and analysis we describe the GUI- and Java-based methods available, including a GUI for query construction and execution, and an automatically generated schema-conforming Java API for processing of annotations. Additionally, we present some specific annotation and research tasks for which NOMOS has been specialized and used, annotation and research tasks for which NOMOS has been specialized and used, including topic segmentation and decision-point annotation of meetings.