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94 - Decompositional Semantics, with Aaron White
NLP Highlights
English - September 30, 2019 22:33 - 27 minutes - 25.5 MB - ★★★★★ - 22 ratingsScience Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Previous Episode: 93 - NLP/ML for clinical data, with Alistair Johnson
Next Episode: 95 - Common sense reasoning, with Yejin Choi
In this episode, Aaron White tells us about the decompositional semantics initiative (Decomp), an attempt to re-think the prototypical approach to semantic representation and annotation. The basic idea is to decompose complex semantic classes such as ‘agent’ and ‘patient’ into simpler semantic properties such as ‘causation’ and ‘volition’, while embracing the uncertainty inherent in language by allowing annotators to choose answers such as ‘probably’ or ‘probably not’. In order to scale the collection of labeled data, each property is annotated by asking crowd workers intuitive questions about phrases in a given sentence.
Aaron White's homepage: http://aaronstevenwhite.io/
Decomp initiative page: http://decomp.io/