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ENTYFI: Entity Typing in Fictional Texts Dependencies Required Data Configuration How to Run Notes
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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/fifa/entyfi

Dependencies

  • Maven, Java 1.8
  • Python2 for mention detection.
    • cPickle
    • theano
  • python3 with tensorflow for fictional typing
    • tensorflow
    • sklearn
    • pandas
    • keras
  • python3 for ultra-fine typing and ilp

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