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Status](https://travis-ci.org/quadrama/DramaNLP.svg?branch=master)](https://travis-ci.org/quadrama/DramaNLP)\n[![DOI](https://www.zenodo.org/badge/57984264.svg)](https://www.zenodo.org/badge/latestdoi/57984264)\n[![license](https://img.shields.io/badge/license-Apache%202-blue.svg)](https://github.com/quadrama/DramaNLP/blob/master/LICENSE)\n\n# DramaNLP\nThis repository contains a number of UIMA components to process dramatic texts, as well as an executable pipeline. We follow general design ideas implemented in [DKPro Core](https://dkpro.github.io/dkpro-core/). The full pipeline reads in files in several TEI/XML dialects (see below), and applies the most important NLP tools on them, while keeping the structural annotation of the plays intact (and, if necessary, processing different text layers separately).\n\n## Compiling from source\n\n1. Clone the repository: `git clone https://github.com/quadrama/DramaNLP.git`\n1. Enter the directory: `cd DramaNLP`\n\t- If necessary, switch to a branch `git checkout develop/1.0`\n1. Download dependencies, compile everything and install it locally: `mvn compile install`\n\tThis produces a lot of output, but at the end, you should see something like `BUILD SUCCESS`\n1. To compile a runnable binary, enter the directory: `cd de.unistuttgart.ims.drama.main` and run `mvn package`. This creates a file called `drama.Main.jar` in the directory `target/assembly/`. This file contains the code and all its dependencies.\n\n\n## Running entire pipeline\n\nAs an example, we'll work on the data from the GerDraCor collection (which is based on TextGrid). Download the files from [GitHub](https://github.com/quadrama/gerdracor) and store the XML files in a directory. We will call the directory `$TEIDIR` in the following examples. The directory `$OUTDIR` is used to store the output of the pipeline. 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