Neural Entity Typing with Knowledge Attention

This repo contains the source code and dataset for the following paper:

Ji Xin, Yankai Lin, Zhiyuan Liu, Maosong Sun. Improving Neural Fine-Grained Entity Typing with Knowledge Attention. The 32nd AAAI Conference on Artificial Intelligence (AAAI 2018).

How to use our code for KNET

All the codes are tested under Ubuntu 16.04.

Data files should be put in the data/ folder.

disamb_file, containing information for disambiguation, is already in data/. Please unzip it.
Train, valid and test set data are also in data/. Please unzip them.
For the word vector file, we recommend using Glove from http://nlp.stanford.edu/data/glove.840B.300d.zip . Please download, unzip, and put it in data/.
types records all they types in the taxonomy (only for recording; not used in the code).

Parameters saved from training is in the parameter/ folder, but you can also choose a new location.
We provide parameters for the model shown in our paper in the paper_parameter/ folder.

Detailed usage can be found by running python src/run.py --help.

Quick start: simply run ./run.sh.