ARCII-for-Matching-Natural-Language-Sentences
A simple version of ARC-II model implemented in Keras.
Please reference paper：Convolutional Neural Network Architectures for Matching Natural Language Sentences
Quick Glance
- Input Data Format
- Train set:
label |q1 |q2
1 |Amrozi accused his brother, whom he called "the witness", of deliberately distorting his evidence. |Referring to him as only "the witness", Amrozi accused his brother of deliberately distorting his evidence.
0 |Yucaipa owned Dominick's before selling the chain to Safeway in 1998 for $2.5 billion. |Yucaipa bought Dominick's in 1995 for $693 million and sold it to Safeway for $1.8 billion in 1998.
- Test set:
q1 |q2
Amrozi accused his brother, whom he called "the witness", of deliberately distorting his evidence. |Referring to him as only "the witness", Amrozi accused his brother of deliberately distorting his evidence.
Yucaipa owned Dominick's before selling the chain to Safeway in 1998 for $2.5 billion. |Yucaipa bought Dominick's in 1995 for $693 million and sold it to Safeway for $1.8 billion in 1998.
- Word Embedding:
word |embedding (300-dimension)
Amrozi |-0.54645991 2.28509140 ... -0.34052843 -2.01874685
chief |-9.01635551 -3.80108356 ... 1.86873138 2.14706421
- Train the model
$ python arcii.py
- Loss and Accuracy
A toy data set example copied from MatchZoo's toy example
Requirements
- Python 3.5
- TensorFlow 1.8.0
- Keras 2.1.6
To do list
- Negative Sampling
- Mask zero inputs