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Add sample labeling config
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pausing_annotator/pause.html

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<View>
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<Text name="text" value="$text"/>
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<View style="box-shadow: 2px 2px 5px #999; padding: 20px; margin-top: 2em; border-radius: 5px;">
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<Header value="What is the sentiment of this text?" />
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<Choices name="sentiment" toName="text" choice="single" showInLine="true">
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<Choice value="positive" hotkey="1" />
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<Choice value="negative" hotkey="2" />
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<Choice value="neutral" hotkey="3" />
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</Choices>
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<Header value="Why?" />
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<TextArea name="comment" toName="text" rows="4" placeholder="Add your comment here..." />
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</View>
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</View><!-- {
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"data": {
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"text": "This is a great movie!"
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}
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} -->
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<!-- Explanation:
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This labeling configuration is designed to allow annotators to
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evaluate the sentiment of a given text while also providing an option
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for additional comments. The configuration includes the following key
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components:
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1. **Text Tag**: The `<Text>` tag displays the text that
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needs to be annotated. It binds to the `value` parameter using the
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variable `$text`, which will be populated with the actual text data
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during annotation.
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2. **Header Tag**: The `<Header>` tag provides a
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title or instruction for the annotators, indicating that they should
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choose the sentiment of the text.
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3. **Choices Tag**: The `<Choices>`
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tag allows annotators to select a sentiment from predefined options.
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In this case, the choices are "Positive" and "Negative". The `toName`
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attribute links this choice to the `text` object, ensuring that the
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sentiment is directly associated with the displayed text.
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4.
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**TextArea Tag**: The `<TextArea>` tag is added to allow annotators to
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provide additional comments or feedback related to their sentiment
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choice. This tag is also linked to the `text` object, ensuring that
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all annotations are connected to the same text input. The `rows`
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attribute specifies the height of the text area, and the `placeholder`
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attribute provides a hint to the annotators about what to enter.
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Overall, this configuration enhances the annotation process by
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allowing for both sentiment classification and qualitative feedback,
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making it a comprehensive tool for text analysis.
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-->

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