65 - Event Representations with Tensor-based Compositions, with Niranjan Balasubramanian

AAAI 2018 paper by Noah Weber, Niranjan Balasubramanian, and
Nathanael Chambers Niranjan joins us on the podcast to tell us
about his latest contribution in a line of work going back to
Shank's scripts. This work tries to model sequences of events to
get coherent narrative schemas, mined from large collections of
text. For example, given an event like "She threw a football", you
might expect future events involving catching, running, scoring,
and so on. But if the event is instead "She threw a bomb", you
would expect future events to involve things like explosions,
damage, arrests, or other related things. We spend much of our
conversation talking about why these scripts are interesting to
study, and the general outline for how one might learn these
scripts from text, and spend a little bit of time talking about the
particular contribution of this paper, which is a better model that
captures interactions among all of the arguments to an event.
https://www.semanticscholar.org/paper/Event-Representations-With-Tensor-Based-Weber-Balasubramanian/418f405a60b8d9009099777f7ae37f4496542f90