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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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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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+
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+
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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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