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            "Programming Language :: Python :: 3",
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        "description": "# Figurenerkennung for German literary texts\n\n[![Build Status](https://travis-ci.com/severinsimmler/figur.svg?branch=master)](https://travis-ci.com/severinsimmler/figur)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2592472.svg)](https://doi.org/10.5281/zenodo.2592472)\n\n\nAn important step in the quantitative analysis of narrative texts is the automatic recognition of references to figures, a special case of the generic NLP problem of Named Entity Recognition (NER).\n\nUsually NER models are not designed for literary texts resulting in poor recall. This easy-to-use package is the continuation of the work of [Jannidis et al.](https://opus.bibliothek.uni-wuerzburg.de/opus4-wuerzburg/frontdoor/deliver/index/docId/14333/file/Jannidis_Figurenerkennung_Roman.pdf) using techniques from the field of Deep Learning.\n\n\n## Installation\n\n```\n$ pip install figur\n```\n\n\n## Example\n\n```python\n>>> import figur\n>>> text = \"Der G\u00e4rtner entfernte sich eilig, und Eduard folgte bald.\"\n>>> figur.tag(text)\n   SentenceId      Token      Tag\n0           0        Der        _\n1           0    G\u00e4rtner  AppTdfW\n2           0  entfernte        _\n3           0       sich     Pron\n4           0     eilig,        _\n5           0        und        _\n6           0     Eduard     Core\n7           0     folgte        _\n8           0      bald.        _\n```\n\n\n## Figurenerkennung statistics\n![Confusion Matrix](doc/confusion-matrix.svg)",
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