Commonsense knowledge about the typical
functions of physical objects allows people to
make inferences during sentence understanding.
For example, we infer that "Sam enjoyed
the book" means that Sam enjoyed reading the
book, even though the action is implicit. Prior
research has focused on learning the prototypical
functions of physical objects in order to
enable inferences about implicit actions. But
many sentences refer to objects even when they
are not used (e.g., "The book fell"). We argue
that NLP systems need to recognize whether an
object is being used before inferring how the
object is used. We define a new task called Object
Use Classification that determines whether
a physical object mentioned in a sentence was
used or likely will be used. We introduce a new
dataset for this task and present a classification
model that exploits data augmentation methods
and FrameNet when fine-tuning a pre-trained
language model. We also show that object use
classification combined with knowledge about
the prototypical functions of objects has the
potential to yield very good inferences about
implicit and anticipated actions.

Identifying Physical Object Use in Sentences

**Topics:** Commonsense Reasoning 
Computational Social Science and Cultural Analytics 
Dialogue and Interactive Systems 
Efficient Methods for NLP 
Ethics 
Demo: Computational social science

Virtual Poster Session 1

poster

## Welcome to EMNLP 2022!
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***EMNLP 2022 General Chair***
 
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EMNLP 2022

Welcome!
EMNLP 2022 will take place in Abu Dhabi from December 7th to December 11th, 2022. And it will be held in hybrid mode, both online and offline.

Tianyu Jiang

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Identifying Physical Object Use in Sentences

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