Update the Readme with additional installation instructions

NOTICE.txt

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+-------------------------------------------------------------------------------
+Copyright 2019
+Ubiquitous Knowledge Processing (UKP) Lab
+Technische Universität Darmstadt
+
+-------------------------------------------------------------------------------
+Third party legal information
+
+

README.md

@@ -1,16 +1,15 @@
-![2010-07-07_ukp_banner](https://user-images.githubusercontent.com/29311022/27184688-27629126-51e3-11e7-9a23-276628da2430.png)
+<img src="https://user-images.githubusercontent.com/29311022/27184688-27629126-51e3-11e7-9a23-276628da2430.png" height=70px/>
+<img src="https://user-images.githubusercontent.com/29311022/27278631-2e19f99e-54e2-11e7-919c-f89ae0c90648.png" height=70px/>
+<img src="https://user-images.githubusercontent.com/29311022/27184769-65c6583a-51e3-11e7-90e0-12a4bdf292e2.png" height=70px/>
 
-![aiphes_logo - small](https://user-images.githubusercontent.com/29311022/27278631-2e19f99e-54e2-11e7-919c-f89ae0c90648.png)
-![tud_weblogo](https://user-images.githubusercontent.com/29311022/27184769-65c6583a-51e3-11e7-90e0-12a4bdf292e2.png)
+# Multi-Sentence Textual Entailment for Claim Verification
+## This repository was constructed by team Athene for the [FEVER shared task 1](http://fever.ai/2018/task.html). The system reached the third rank in the overall results and first rank on the evidence recall sub-task
 
+This repository builds upon the baseline system repository developed by the FEVER shared task organizers: https://github.com/sheffieldnlp/fever-naacl-2018
 
-## This repository was constructed by team Athene for the FEVER shared task 1 (http://fever.ai/2018/task.html)
-### The system reached the third rank in the overall results and first rank on the evidence recall sub-task
+This is an accompanying repository for our FEVER Workshop paper at EMNLP 2018. For more information see the paper: [UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification](https://arxiv.org/pdf/1809.01479.pdf)
 
-This repository builts upon the baseline system repository developed by the FEVER shared task organizers: (https://github.com/sheffieldnlp/fever-naacl-2018)
-
-For more information see our paper: [UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification](https://arxiv.org/pdf/1809.01479.pdf)
-* BibTeX:
+Please use the following citation:
 
             @article{hanselowski2018ukp,
                       title={UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification},
@@ -20,11 +19,34 @@ For more information see our paper: [UKP-Athene: Multi-Sentence Textual Entailme
                     }
 
 
+Disclaimer:
+> This repository contains experimental software and is published for the sole purpose of giving additional background details on the respective publication.
+
 
+### Requirements
+* Python 3.6
+* AllenNLP
+* TensorFlow
 
+### Installation 
 
+* Download and install Anaconda (https://www.anaconda.com/)
+* Create a Python Environment and activate it:
+```bash 
+    conda create -n fever python=3.6
+    source activate fever
+```
+* Install the required dependencies
+```bash
+    pip install -r requirements.txt
+```
+* Download NLTK Punkt Tokenizer
+```bash
+    python -c "import nltk; nltk.download('punkt')"
+```
+* Proceed with downloading the data set, the embeddings, the models and the evidence data
 
-## Download Data
+### Download the FEVER data set
 Download the FEVER dataset from [the website of the FEVER share task](https://sheffieldnlp.github.io/fever/data.html) into the data directory
 
     mkdir data
@@ -34,7 +56,10 @@ Download the FEVER dataset from [the website of the FEVER share task](https://sh
     wget -O data/fever-data/train.jsonl https://s3-eu-west-1.amazonaws.com/fever.public/train.jsonl
     wget -O data/fever-data/dev.jsonl https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_dev.jsonl
     wget -O data/fever-data/test.jsonl https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_test.jsonl
-
+
+
+### Download the word embeddings
+
 Download pretrained GloVe Vectors
 
     wget http://nlp.stanford.edu/data/wordvecs/glove.6B.zip
@@ -47,40 +72,46 @@ Download pretrained Wiki FastText Vectors
     mkdir -p data/fasttext
     unzip wiki.en.zip -d data/fasttext
 
-## Create Python Environment
-    conda create -n fever python=3.6
-    source activate fever
-    pip install -r requirements.txt
-
-
-Download NLTK Punkt Tokenizer
 
-    python -c "import nltk; nltk.download('punkt')"
-
-## Data Preparation
-The data preparation consists of three steps: downloading the articles from Wikipedia, indexing these for the Evidence Retrieval and performing the negative sampling for training . 
+### Download evidence data
+The data preparation consists of three steps: (1) downloading the articles from Wikipedia, (2) indexing these for the evidence retrieval and (3) performing the negative sampling for training . 
 
-### 1. Download Wikipedia data:
+#### 1. Download Wikipedia data:
 
 Download the pre-processed Wikipedia articles and unzip it into the data folder.
 
     wget https://s3-eu-west-1.amazonaws.com/fever.public/wiki-pages.zip
     unzip wiki-pages.zip -d data
 
 
-### 2. Indexing 
+#### 2. Indexing 
 Construct an SQLite Database (go grab a coffee while this runs)
 
     PYTHONPATH=src python src/scripts/build_db.py data/wiki-pages data/fever/fever.db
+
+#### 3. Sampling negative evidence
+[coming soon]
 
 
-## Run the end to end pipeline of the submitted models
+### Download the UKP-Athene models
+[coming soon]
+
+### Run the end-to-end pipeline of the submitted models
 
     PYTHONPATH=src python src/script/athene/pipeline.py
 
-## Run the variation of the RTE model
+### Run the variation of the RTE model
 Another variation of the ESIM model is configured through the config file in the conf folder.
 
 To run the models:
 
-    PYTHONPATH=src python src/scripts/athene/pipeline.py --config conf/<config_file>
+    PYTHONPATH=src python src/scripts/athene/pipeline.py --config conf/<config_file>
+
+### Contacts:
+If you have any questions regarding the code, please, don't hesitate to contact the authors or report an issue.
+  * \<lastname\>@ukp.informatik.tu-darmstadt.de
+  * https://www.informatik.tu-darmstadt.de/ukp/ukp_home/
+  * https://www.tu-darmstadt.de    
+
+### License:
+  * Apache License Version 2.0