type DependencyScorerI

Overrides: object.__init__

(inherited documentation)

Parameters:

• graphs (A list of DependencyGraph) - A list of dependency graphs to train the scorer. Typically the edges present in the graphs can be used as positive training examples, and the edges not present as negative examples.

@type graph: A C{DependencyGraph}
@param graph: A dependency graph whose set of edges need to be 
scored.  
@rtype: A three-dimensional list of numbers.
@return: The score is returned in a multidimensional(3) list, such
that the outer-dimension refers to the head, and the
inner-dimension refers to the dependencies.  For instance,  
scores[0][1] would reference the list of scores corresponding to 
arcs from node 0 to node 1.  The node's 'address' field can be used 
to determine its number identification.

For further illustration, a score list corresponding to Fig.2 of 
Keith Hall's 'K-best Spanning Tree Parsing' paper:
      scores = [[[], [5],  [1],  [1]],
               [[], [],   [11], [4]],
               [[], [10], [],   [5]],
               [[], [8],  [8],  []]]
When used in conjunction with a MaxEntClassifier, each score would 
correspond to the confidence of a particular edge being classified 
with the positive training examples.

Overrides: object.__hash__

(inherited documentation)