49 - A Joint Sequential and Relational Model for Frame-Semantic Parsing, with Bishan Yang - a podcast by Allen Institute for Artificial Intelligence

EMNLP 2017 paper by Bishan Yang and Tom Mitchell.

Bishan tells us about her experiments on frame-semantic parsing / semantic role labeling, which is trying to recover the predicate-argument structure from natural language sentences, as well as categorize those structures into a pre-defined event schema (in the case of frame-semantic parsing). Bishan had two interesting ideas here: (1) use a technique similar to model distillation to combine two different model structures (her "sequential" and "relational" models), and (2) use constraints on arguments across frames in the same sentence to get a more coherent global labeling of the sentence. We talk about these contributions, and also touch on "open" versus "closed" semantics, in both predicate-argument structure and information extraction.

https://www.semanticscholar.org/paper/A-Joint-Sequential-and-Relational-Model-for-Frame-Yang-Mitchell/a1deb609e3758519cbe3f1a542bdf1ea52b6f224

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