<h1 align="center">Welcome to the Corpus Annotation Graph Builder <code>(CAG)</code> </h1>
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> `cag` is a Python Library offering an architectural framework to employ the build-annotate pattern when building Graphs.
---
[Official Documentation](https://cagraph.info/).
**Corpus Annotation Graph builder (CAG)** is an *architectural framework* that employs the *build-and-annotate* pattern for creating a graph. CAG is built on top of [ArangoDB](https://www.arangodb.com) and its Python drivers ([PyArango](https://pyarango.readthedocs.io/en/latest/)). The *build-and-annotate* pattern consists of two phases (see Figure below): (1) data is collected from different sources (e.g., publication databases, online encyclopedias, news feeds, web portals, electronic libraries, repositories, media platforms) and preprocessed to build the core nodes, which we call *Objects of Interest*. The component responsible for this phase is the **Graph-Creator**. (2) Annotations are extracted from the OOIs, and corresponding annotation nodes are created and linked to the core nodes. The component dealing with this phase is the **Graph-Annotator**.
This framework aims to offer researchers a flexible but unified and reproducible way of organizing and maintaining their interlinked document collections in a Corpus Annotation Graph.
## Installation
### Direct install via pip
The package can also be installed directly via pip.
```
pip install cag
```
This will allow you to use the module **`cag`** from any python script locally. The two main packages are **`cag.framework`** and **`cag.view_wrapper`**.
### Manual cloning
Clone the repository, go to the root folder and then run:
```
pip install -e .
```
## Citation
Please cite us in case you use CAG
@inproceedings{el-baff-etal-2023-corpus,
title = "Corpus Annotation Graph Builder ({CAG}): An Architectural Framework to Create and Annotate a Multi-source Graph",
author = "El Baff, Roxanne and
Hecking, Tobias and
Hamm, Andreas and
Korte, Jasper W. and
Bartsch, Sabine",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-demo.28",
pages = "248--255"
}
## Usage
* After the installation, a project scaffold can be created with the command `cag start-project`
* Graph Creation [[jupyter notebook](https://github.com/DLR-SC/corpus-annotation-graph-builder/blob/main/examples/1_create_graph.ipynb)]
* Graph Annotation [[jupyter notebook](https://github.com/DLR-SC/corpus-annotation-graph-builder/blob/main/examples/2_annotate_graph.ipynb)]
## Zenodo refs
* v1.5.0 [](https://zenodo.org/badge/latestdoi/572124344)
* v1.4.0 [](https://doi.org/10.5281/zenodo.7701921)
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"description": "\n\n<h1 align=\"center\">Welcome to the Corpus Annotation Graph Builder <code>(CAG)</code> </h1>\n\n<p align=\"center\">\n <a href=\"https://pypi.org/project/cag/\"><img src=\"https://badge.fury.io/py/cag.svg\" alt=\"Badge: PyPI version\" height=\"18\"></a>\n <a href=\"https://img.shields.io/badge/Made%20with-Python-1f425f.svg\">\n <img src=\"https://img.shields.io/badge/Made%20with-Python-1f425f.svg\" alt=\"Badge: Made with Python\"/>\n </a>\n \n\n <a href=\"https://open.vscode.dev/DLR-SC/corpus-annotation-graph-builder\">\n <img alt=\"Badge: Open in VSCode\" src=\"https://img.shields.io/static/v1?logo=visualstudiocode&label=&message=open%20in%20visual%20studio%20code&labelColor=2c2c32&color=007acc&logoColor=007acc\" target=\"_blank\" />\n </a>\n <a href=\"https://github.com/psf/black\"><img src=\"https://img.shields.io/badge/code%20style-black-000000.svg\" alt=\"Badge: Black\" height=\"18\"></a>\n<a href=\"https://zenodo.org/badge/latestdoi/572124344\"><img src=\"https://zenodo.org/badge/572124344.svg\" alt=\"DOI\"></a>\n <a href=\"https://github.com/DLR-SC/corpus-annotation-graph-builder/blob/master/LICENSE\">\n <img alt=\"License: MIT\" src=\"https://img.shields.io/badge/license-MIT-yellow.svg\" target=\"_blank\" />\n </a>\n <a href=\"https://twitter.com/dlr_software\">\n <img alt=\"Twitter: DLR Software\" src=\"https://img.shields.io/twitter/follow/dlr_software.svg?style=social\" target=\"_blank\" />\n </a>\n</p>\n\n\n> `cag` is a Python Library offering an architectural framework to employ the build-annotate pattern when building Graphs.\n\n---\n\n\n\n[Official Documentation](https://cagraph.info/).\n\n**Corpus Annotation Graph builder (CAG)** is an *architectural framework* that employs the *build-and-annotate* pattern for creating a graph. CAG is built on top of [ArangoDB](https://www.arangodb.com) and its Python drivers ([PyArango](https://pyarango.readthedocs.io/en/latest/)). The *build-and-annotate* pattern consists of two phases (see Figure below): (1) data is collected from different sources (e.g., publication databases, online encyclopedias, news feeds, web portals, electronic libraries, repositories, media platforms) and preprocessed to build the core nodes, which we call *Objects of Interest*. The component responsible for this phase is the **Graph-Creator**. (2) Annotations are extracted from the OOIs, and corresponding annotation nodes are created and linked to the core nodes. The component dealing with this phase is the **Graph-Annotator**.\n\n\n\n\n\nThis framework aims to offer researchers a flexible but unified and reproducible way of organizing and maintaining their interlinked document collections in a Corpus Annotation Graph. \n\n## Installation\n\n### Direct install via pip \n\nThe package can also be installed directly via pip.\n```\npip install cag\n```\n\nThis will allow you to use the module **`cag`** from any python script locally. The two main packages are **`cag.framework`** and **`cag.view_wrapper`**.\n\n\n### Manual cloning\nClone the repository, go to the root folder and then run:\n\n```\npip install -e .\n```\n\n## Citation\nPlease cite us in case you use CAG\n\n @inproceedings{el-baff-etal-2023-corpus,\n title = \"Corpus Annotation Graph Builder ({CAG}): An Architectural Framework to Create and Annotate a Multi-source Graph\",\n author = \"El Baff, Roxanne and\n Hecking, Tobias and\n Hamm, Andreas and\n Korte, Jasper W. and\n Bartsch, Sabine\",\n booktitle = \"Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations\",\n month = may,\n year = \"2023\",\n address = \"Dubrovnik, Croatia\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://aclanthology.org/2023.eacl-demo.28\",\n pages = \"248--255\"\n }\n\n\n## Usage\n* After the installation, a project scaffold can be created with the command `cag start-project`\n* Graph Creation [[jupyter notebook](https://github.com/DLR-SC/corpus-annotation-graph-builder/blob/main/examples/1_create_graph.ipynb)]\n* Graph Annotation [[jupyter notebook](https://github.com/DLR-SC/corpus-annotation-graph-builder/blob/main/examples/2_annotate_graph.ipynb)]\n\n\n\n## Zenodo refs\n\n* v1.5.0 [](https://zenodo.org/badge/latestdoi/572124344)\n* v1.4.0 [](https://doi.org/10.5281/zenodo.7701921)\n\n\n",
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