Difference between revisions of "100713Notes"
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| + | : The sentential extraction results for the original Multir Algorithm seem to be different from the results in the paper in that the highest recall difference here is approximately 20 percentage points lower than the recall level reported in the paper. | ||
Revision as of 18:24, 8 October 2013
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
- The sentential extraction results for the original Multir Algorithm seem to be different from the results in the paper in that the highest recall difference here is approximately 20 percentage points lower than the recall level reported in the paper.
