Today we continue our discussion on natural language processing with a particular word ontology called FrameNet. We see how it is different from other ontologies. For example, FrameNet differs from WordNet in the lexical information and is in fact, complimentary in many ways. FrameNet has far fewer nouns, verbs, adjectives and adverbs as compared to WordNet. FrameNet Frame hierarchies provide better generalizations than WordNet synset hierarchies.
FrameNet also differs from PropBank (Proposition Bank discussed by Palmer et al 2005). PropBank began with labeling verbs and their arguments.
FrameNet assigns names such as communicator, evaluee and reason for corresponding PropBank role labels.
There have been other works to represent semantic information such as Abstract Meaning Representation ( Banarescu et al, Law 2013). AMR is a graph based representation of lexical concepts and typed relations between those concepts that are denoted by an English sentence.
However the lexical semantics in FrameNet are much deeper than AMR
What AMR means for Framenet and for our use is that we can represent the Frames in a graph where the relationships are persisted. These edges can then be traversed.  Previously we used graphs with edges established based on similarity measures. Here we establish edges based on the relationships between frames.

#codingexercise
Find the number of islands of 1 in a binary matrix comprising of 0 and 1. In other words, count the number of connected components in an undirected graph.
int GetCountOfIslands(int[,] m, int row, int col)
{
bool visited = new bool[row,col]; // initialized to False
int count = 0;
for (int I = 0; I < row; I ++)
   for (int j = 0; j < col; j++)
       if (m[i.j] == 1 && visited[i,j] == False)
      {
             DFS(m, I, j, visited);
             count++;
      }
 return count;
}
int DFS(int[,] m, int row, int col, bool[,] visited)
{
var radj = new int[] {-1, -1, -1,  0, 0,  1, 1, 1};
var cadj = new int[] {-1,  0,  1, -1, 1, -1, 0, 1};
visited [row,col] = true;
for (int k  = 0; k < 8; k++)
   if (withinMatrixAndNotVisited(m, row + radj[k], col + cadj[k], visited))
      DFS (m, row + radj[k], col + cadj[k], visited);
}
We can also measure the size of each island with a minor modification to above.