The process of annotating text corpora involves establishing annotation schemata which define the scope and depth of an annotation task at hand. We demonstrate this activity in Argo, a Web-based workbench for the analysis of textual resources, which facilitates both automatic and manual annotation. Annotation tasks in the workbench are defined by building workflows consisting of a selection of available elementary analytics developed in compliance with the Unstructured Information Management Architecture specification. The architecture accommodates complex annotation types that may define primitive as well as referential attributes. Argo aids the development of custom annotation schemata and supports their interoperability by featuring a schema editor and specialised analytics for schemata alignment. The schema editor is a self-contained graphical user interface for defining annotation types. Multiple heterogeneous schemata can be aligned by including one of two type mapping analytics currently offered in Argo. One is based on a simple mapping syntax and, although limited in functionality, covers most common use cases. The other utilises a well established graph query language, SPARQL, and is superior to other state-of-the-art solutions in terms of expressiveness. We argue that the customisation of annotation schemata does not need to compromise their interoperability.

Challenges in creating comprehensive text-processing worklows include a lack of the interoperability of individual components coming from different providers and/or a requirement imposed on the end users to know programming techniques to compose such workflows. In this paper we demonstrate Argo, a web-based system that addresses these issues in several ways. It supports the widely adopted Unstructured Information Management Architecture (UIMA), which handles the problem of interoperability; it provides a web browser-based interface for developing workflows by drawing diagrams composed of a selection of available processing components; and it provides novel user-interactive analytics such as the annotation editor which constitutes a bridge between automatic processing and manual correction. These features extend the target audience of Argo to users with a limited or no technical background. Here, we focus specifically on the construction of advanced workflows, involving multiple branching and merging points, to facilitate various comparative evalutions. Together with the use of user-collaboration capabilities supported in Argo, we demonstrate several use cases including visual inspections, comparisions of multiple processing segments or complete solutions against a reference standard, inter-annotator agreement, and shared task mass evaluations. Ultimetely, Argo emerges as a one-stop workbench for defining, processing, editing and evaluating text processing tasks.