50 - Cardinal Virtues: Extracting Relation Cardinalities from Text, with Paramita Mirza

ACL 2017 paper, by Paramita Mirza, Simon Razniewski, Fariz Darari,
and Gerhard Weikum. There's not a whole lot of work on numbers in
NLP, and getting good information out of numbers expressed in text
can be challenging. In this episode, Paramita comes on to tell us
about her efforts to use distant supervision to learn models that
extract relation cardinalities from text. That is, given an entity
and a relation in a knowledge base, like "Barack Obama" and "has
child", the goal is to extract _how many_ related entities there
are (in this case, two). There are a lot of challenges in getting
this to work well, and Paramita describes some of those, and how
she solved them.
https://www.semanticscholar.org/paper/Cardinal-Virtues-Extracting-Relation-Cardinalities-Mirza-Razniewski/01afba9f40e0df06446b9cd3d5ea8725c4ba1342