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

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

**The podcast is currently on hiatus. For more active NLP content, check out the Holistic Intelligence Podcast linked below.**

Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. All views expressed belong to the hosts/guests, and do not represent their employers.

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

NLP Highlights