Today we continue our discussion on natural language processing with a particular word ontology called FrameNet.
Framenet is a lexical database maintained by Berkeley.
It has the following features:
It has annotations about how words are used in actual text.
It can be used like a dictionary.
It has over 170000 annotated sentences describing word usage
It provides a unique training data set
It is both human readable and machine readable.
The data is freely available to download.
The annotations show how words have unique combinations.
FrameNet defines the idea that words have a meaning based on the presence of a semantic frame. This is a type of event, relation or entity and the participants in it. The example cited is that of cooking. The concept of cooking typically involves a person doing the cooking (cook) and the food that is cooked (food) and something to hold (container) along with a source of heat (heating instrument) This is represented as a frame called 'Apply_heat' where the frame elements are the cook, food, container and heating_instrument. The frame units then naturally fit as superimposed on the words that evoke them.
The frame units help with both semantic and syntactic relationships. As such they are better representations than terms themselves while allowing the models based on those terms to work as before, if not improved with the frame elements.
Framenet is a lexical database maintained by Berkeley.
It has the following features:
It has annotations about how words are used in actual text.
It can be used like a dictionary.
It has over 170000 annotated sentences describing word usage
It provides a unique training data set
It is both human readable and machine readable.
The data is freely available to download.
The annotations show how words have unique combinations.
FrameNet defines the idea that words have a meaning based on the presence of a semantic frame. This is a type of event, relation or entity and the participants in it. The example cited is that of cooking. The concept of cooking typically involves a person doing the cooking (cook) and the food that is cooked (food) and something to hold (container) along with a source of heat (heating instrument) This is represented as a frame called 'Apply_heat' where the frame elements are the cook, food, container and heating_instrument. The frame units then naturally fit as superimposed on the words that evoke them.
The frame units help with both semantic and syntactic relationships. As such they are better representations than terms themselves while allowing the models based on those terms to work as before, if not improved with the frame elements.
#codingexercise
Insert a node into a sorted circular linked list
Void insertCircular(ref node head, node target)
{
If (head == null) {head = target; target.next =
target; return;}
Node prev = null;
Node curr = head;
while(curr.data < target.data &&
curr.next != head){
Prev = curr;
Curr = curr.next;
}
If (prev ==
null){
If (curr.data
< target.data){
InsertAt(cur, target);
}else{
InsertAtStart(head, target);
}
}else{
if
(curr.data < target.data) {
InsertAt(cur, target);
}else{
InsertAt(prev, target);
}
}
}
void InsertAt(ref node head, ref target)
{
// Insert After head
var next = head.next;
target.next = next;
head.next = target;
}
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