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uPick: Cro wdso urcing Based Approac h to Extract Relations Among Named Entities Deepti Aggarwal, Rohit Ashok Khot, Vasudeva Varma & Venkatesh Choppe lla

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Page 1: 5min presentation

uPick: Crowdsourcing Based Approach to

Extract Relations Among Named Entities

Deepti Aggarwal, Rohit Ashok Khot,

Vasudeva Varma & Venkatesh Choppella

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“You see sir, I can talk English, I can walk English, I can laugh English, I can run English, because

English is such a funny language.”Amitabh in Namak Halal

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See an example…

“Tom called his father last night. They

talked for an hour. He said he would be home the next day."

What is ‘He' referring to? Tom or his father?

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Named entity Relationship: An Example

Sachin Tendulkar was born in Bombay

Subject Relation Object

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Challenges of language structure

Co-reference resolution

Ambiguous, complex sentences

Abbreviations

Acronyms

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Existing Approaches

NLP based

Machine Learning based

Statistical Methods

Others

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How to resolve?

Dependency issues

Scalability issues

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Can we do better?

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Our idea: Bring humans in the loop

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You are most welcome!