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-# ENTYFI
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+# ENTYFI: Entity Typing in Fictional Texts
+
+Cuong Xuan Chu, Simon Razniewski, Gerhard Weikum. (WSDM 2020)
+Project website: https://www.mpi-inf.mpg.de/yago-naga/entyfi
+
+# Dependencies
+- Python2 for mention detection.
+  - cPickle
+  - theano
+- python3 with tensorflow for fictional typing
+  - tensorflow
+  - sklearn
+  - pandas
+  - keras
+- python3 for ultra-fine typing and ilp
+  - Pytorch (ver 0.3.0)
+  - Python3 
+  - Numpy
+  - Tensorboard 
+  - Pickle
+  - ast, pulp
+  - Pretrained word embeddings: "wget http://nlp.stanford.edu/data/glove.840B.300d.zip".
+  
+# Required Data
+You need to download required data which include background knowledge bases of all reference universes, pretrained models for fictional typing module and data for reference universe ranking. 
+
+All data can be found at: http://people.mpi-inf.mpg.de/~cxchu/entyfi/
+
+# Configuration
+To run typing, you need to set some paths in several files:
+- ultrafile/resources/constant.py
+  - GLOVE_VEC=path to pretrained word embedding (glove)
+- utils/Constants.java
+  - PYTHON_TAGGER=path to python2 for mention detection
+  - PYTHON_ULTRA=path to python3 for ultra-fine typing and ilp
+  - PYTHON_GENERALTYPING=path python3 with tensorflow for fictional typing
+- resources/wikia.properties
+  - BASE_DIR=path to data-store (background KB of all universes) --- data-store (downloaded data)
+  - ATTENTION_MODEL=path to pretrained model of fictional typing module --- attentionModel (downloaded data)
+  - TERMATRIX=path to universe-term matrix for reference universe ranking --- universe-termmatrix (downloaded data)
+
+# How to Run
+
+- Build: ./build.sh
+- Run typing: ./run.sh heap-size typing.ENTYFI input-file output-file
+  For example: ./run.sh 10G typing.ENTYFI input-file output-file
+Other parameters like topK reference universes or topK types returned by ILP can be defined in class typing/ENTYFI.java
+
+# Notes
+
+- For mention detection, to improve efficiency, we use technique from the paper: https://arxiv.org/abs/1603.01360