100713Notes

Goals

1. Run and compare Mihai's reimplementation of Multir with Original Multir on protobuf train and test input
2. Reimplement Distant Supervision component

• Rewrite distant supervision code in Java
• Have modules for semantic databases and training corpora
• Separate the process of training instance collection from feature generation
• Reimplement Multir input interface to deal with new training data format

Log

October 8 2013

Compared Mihai's reimplementation of Multir and the original Multir algorithm

Aggregate Extraction Precision/Recall Table at Highest Recall Level

Algorithm	Precision	Recall
Mihai's Reimplementation	.328	.183
Original Multir	.372	.180

This will serve as a benchmark as I try to refactor the Multir code into a more usable code base.

Sentential Extraction Precision/Recall Table for Original Multir Algorithm at Highest Recall Level

Precision	Recall
.843	.325