welcome!
i research machine learning for natural language processing and i like full-stack development
An implementation of (Chambers and Jurafsky, 2008), using updated machine learning models, and different training data domains for an independent study at the University of Pennsylvania.
Home Page: https://kirubarajan.com/blog/narrative
License: MIT License
welcome!
i research machine learning for natural language processing and i like full-stack development
Hi Arun,
This looks like a great system! Thank you for making it available under the MIT license!
I installed it today (noting that it took a while to install pymagnitude), however when I went to run the preexisting model on sample input, neither the model.pickle nor data/input1.txt were there. I was wondering whether these files were available somewhere, or if not, how to generate them? I saw that it may depend on having the Annotated Gigaword here (https://catalog.ldc.upenn.edu/LDC2012T21). Is it correct that I need to obtain this dataset in order to generate the model? Also, what is the format of the input1.txt file?
Thanks!
I'm trying to extract narrative chains to mine typical responses to previous actions for how people respond to difficult situations such as domestic violence, and then generate Monte-Carlo simulations based on the possible responses:
consider(B,do(B,issueWarningOfConsequences(B,A))) :-
believe(B,do(A,physicallyAttack(A,B))).
consider(B,do(B,fileAPoliceReportAbout(B,A))) :-
believe(B,do(A,physicallyAttack(A,B))).
Once these simulations are running, I can begin constructing professionally recommended responses using a BDI agent. Once these good responses are created, the system can then function as a real-time decision aid to people in difficult situations.
Regards,
Andrew
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