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Smoothing Entailment Graphs with Language Models Nick McKenna Tianyi Li Mark Johnson Mark Steedman University of Edinburgh Macquarie University nick.mckenna@ed.ac.uk tianyi.li@ed.ac.uk mark.johnson@mq.edu.au

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How to fill out smoothing entailment graphs with

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Understand the purpose of smoothing entailment graphs

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Identify the nodes and edges in the graph

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Who needs smoothing entailment graphs with?

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Researchers working in the field of natural language processing

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Data scientists analyzing large sets of text data

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Smoothing entailment graphs involve the process of adjusting data to create a more uniform representation, minimizing abrupt changes and enhancing interpretability.

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Entities that generate or utilize entailment graphs for reporting purposes, such as companies and organizations involved in data analysis or regulatory compliance, are typically required to file smoothing entailment graphs.

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The purpose of smoothing entailment graphs is to clarify trends in data, reduce noise, and allow for better analysis and decision-making by providing a clearer visual representation of underlying relationships.

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Smoothing entailment graphs must report relevant data points, normalization techniques used, the period of the data analysis, and any assumptions made during the smoothing process.

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