Automated Template Extraction

Team Member(s)

• Francis Keith
• Andrew Rodriguez
• Anyone else who may be interested

Proposal

Template-based information extraction methods have one glaring weakness: they rely on - you guessed it - templates. These templates are often hand-crafted, and thus either require a significant amount of time and painstaking tuning, or they are prone to errors. Neither of these alternatives is ideal, so it would be beneficial if we could automatically produce these templates from data.

The paper referenced below by Chambers and Jurafsky is what I plan to use as a "jumping-off" point, so to speak.

I'd like to look more into the paper's methodology, apply it to a new domain, and potentially improve upon some methodology that is used.

Baseline

Given that this is a fairly novel approach, I'm not sure how easy it will be to find a baseline. I suppose it will depend on the final project methodology - if the focus is solely on the automated template extraction, it would be reasonable to attempt to compare a standard IE system and "hand-written" or some other "gold standard" templates with the automatically generated templates. It's something that will need to be given some thought.

Dataset

I'm still hunting around for a good dataset to use for this problem.

The Chambers and Jurafsky paper uses the MUC 4 data set on terrorism. We could use any of the MUC datasets. General MUC dataset information.

Related Work

• Template-Based Information Extraction without the Templates by Nathanael Chambers and Dan Jurafsky