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Placeholder

As explained in Data Analysis with LLMs

A missing-value placeholder is a marker stored in place of a value that is unavailable in an extracted record.

A missing-value placeholder marks an attribute that cannot be found in the source text. It keeps that attribute’s position in an extracted record without supplying a value the text does not provide. section 4.3.2 section 4.3.5

For a table extracted from emails, specify the attributes and their order, then instruct the language model to write <NA> whenever an attribute’s value is unavailable. This is different from a prompt-template placeholder, such as [Email]: [Email] is replaced before the prompt is sent; <NA> appears in the extracted output. section 4.3.2 section 1.4.1

A biography with no birth city

A biography extraction requests name, city of birth, and date of birth. When a biography snippet gives no birth city, its output row contains <NA> in that field rather than a concrete city. section 4.3.5

 #1
Extract the following properties into a table:
[List of attributes] 
 #2
Text source: [Email] 
 #3
Mark the beginning of the table with <BeginTable> and the end with <EndTable>.
Separate rows by newline symbols and separate fields by pipe symbols (|).
Omit the table header and insert values in the attribute order from above.
Use the placeholder <NA> if the value for an attribute is not available.

The prompt specifies attribute order, table delimiters, and the exact marker to use for unavailable values. section 4.3.2

How Data Analysis with LLMs covers it

How deep it goes
Shows an explicit prompt instruction and a resulting missing field, but does not describe downstream handling of the marker.
Examples
Uses <NA> for an unavailable attribute and for a birth city absent from a biography snippet.
What you can do after
Build it from scratch by instructing a language model to place <NA> in unavailable fields of an extracted table.
How it connects
Connects text extraction, prompt templates, table formatting, and CSV output.

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