MaltParser has the possibility of distinguishing between different kinds of null-values when extracting the feature vector. For input columns like `POSTAG` it is possible to differentiate two null-values:

- `NO NODE`: There exists no corresponding dependency graph node (e.g., because the lookahead extend beyond the end of the string), which means that the feature is really undefined.
- `ROOT NODE`: The dependency graph node is a root node, which means that it is not possible to extract an input column value (for example, the word form or the part-of-speech).

In addition to the two null value categories for input columns, there is one more for the output columns:

- `NO VALUE`: The dependency graph node exists and is not the root, but has not yet been assigned a value for the output column requested (e.g., has not been assigned a head and therefore does not have a dependency type).

With the option `--singlemalt-null_value` it is possible to specify the degree of differentiation of null-values.

- `none`: Excludes all kinds of null-values when extracting the feature vector, this option value is not possible for learning methods that have symbolic feature vector encoding.
- `one`: Maps all kinds of null values to one symbol.
- `rootlabel`: Maps all kinds of null values to one symbol and for output columns this symbol is the same as the root label (used to emulate MaltParser 0.4)
- `rootnode`: Distinguishes between `NO NODE` and `ROOT NODE`, and the `NO VALUE` null-value case is mapped to the `ROOT NODE` null-value for output columns.
- `novalue`: Distinguishes between `NO NODE` and `ROOT NODE` for both input and output columns, and `NO VALUE` for output columns.