[Theory] REMINDER: 3/20 Talks at TTIC: Rachel Rudinger, Johns Hopkins University

[Mary Marre]

When:    Wednesday, March 20th at *11:00 am*

Where:    TTIC, 6045 S Kenwood Avenue, 5th Floor, Room 526

Who:      Rachel Rudinger, Johns Hopkins University


*Title*
Natural Language Understanding for Events and Participants in Text

*Abstract*
Consider the difference between the two sentences “Pat didn’t remember to
water the plants” and “Pat didn’t remember that she had watered the
plants.” Fluent English speakers recognize that the former sentence implies
that Pat did not water the plants, while the latter sentence implies she
did. This distinction is crucial to understanding the meaning of these
sentences, yet it is one that automated natural language processing (NLP)
systems struggle to make. In this talk, I will discuss my work on
developing state-of-the-art NLP models that make essential inferences about
events (e.g., a “watering” event) and participants (e.g., “Pat” and “the
plants”) in natural language sentences. In particular, I will focus on two
supervised NLP tasks that serve as core tests of language understanding:
Event Factuality Prediction and Semantic Proto-Role Labeling. I will also
discuss my work on unsupervised acquisition of common-sense knowledge from
large natural language text corpora, and the concomitant challenge of
detecting problematic social biases in NLP models trained on such data.

Host: Kevin Gimpel <kgimpel at ttic.edu>



Mary C. Marre
Administrative Assistant
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Room 517*
*Chicago, IL  60637*
*p:(773) 834-1757*
*f: (773) 357-6970*
*mmarre at ttic.edu <mmarre at ttic.edu>*


On Fri, Mar 15, 2019 at 11:37 AM Mary Marre <mmarre at ttic.edu> wrote:

> When:    Wednesday, March 20th at *11:00 am*
>
> Where:    TTIC, 6045 S Kenwood Avenue, 5th Floor, Room 526
>
> Who:      Rachel Rudinger, Johns Hopkins University
>
>
> *Title*
> Natural Language Understanding for Events and Participants in Text
>
> *Abstract*
> Consider the difference between the two sentences “Pat didn’t remember to
> water the plants” and “Pat didn’t remember that she had watered the
> plants.” Fluent English speakers recognize that the former sentence implies
> that Pat did not water the plants, while the latter sentence implies she
> did. This distinction is crucial to understanding the meaning of these
> sentences, yet it is one that automated natural language processing (NLP)
> systems struggle to make. In this talk, I will discuss my work on
> developing state-of-the-art NLP models that make essential inferences about
> events (e.g., a “watering” event) and participants (e.g., “Pat” and “the
> plants”) in natural language sentences. In particular, I will focus on two
> supervised NLP tasks that serve as core tests of language understanding:
> Event Factuality Prediction and Semantic Proto-Role Labeling. I will also
> discuss my work on unsupervised acquisition of common-sense knowledge from
> large natural language text corpora, and the concomitant challenge of
> detecting problematic social biases in NLP models trained on such data.
>
> Host: Kevin Gimpel <kgimpel at ttic.edu>
>
>
>
> Mary C. Marre
> Administrative Assistant
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue*
> *Room 517*
> *Chicago, IL  60637*
> *p:(773) 834-1757*
> *f: (773) 357-6970*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
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