Hi all,
My name is Abhishek Tiwari. I am a fourth year undergraduate student at
IIT(BHU),Varanasi. I have been working on my semester project
"Identification of causal relation in natural language text with the help
of graph patterns". This project gave me experience of handling Stanford
parser(for chunking and obtaining parse tree format) and SenseLearner(word
sense disambiguation).
Also I had learnt wide number of python libraries such as lxml, nltk ,
multiprocessing, networkx(for graph representation) and graph-tool. I also
had to use streaming API in Hadoop while writing mapreduce in python in
order to manage large number of computations.
Currently I have been trying the warmup tasks listed for 5.1 Fact
extraction from wikipedia text.
Although I am also interested in NLP topics by dbpedia-spotlight:
5.15 Better Context Vectors
5.16 Better Surface Form Matching
5.19 Confidence/Relevance Scores
I am going to try warmup task for the topics. Please guide as how to best
understand the above topics.
Regards,
Abhishek Tiwari
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