Handling ambiguity

When we jump into semantic analysis, we may find there are many cases that are too ambiguous for an NLP system to handle. In these cases, we need to know what kinds of ambiguity exist and how we can handle them.

Ambiguity is one of the areas of NLP and cognitive sciences that doesn't have a well-defined solution. Sometimes, sentences are so complex and ambiguous that only the speaker can define the original or definite meaning of the sentence.

A word, phrase, or sentence is ambiguous if it has more than one meaning. If we consider word light,than it can mean not very heavy or not very dark. This is word level ambiguity. The phrase porcelain egg container is structure level ambiguity. So, here we will see different types of ambiguities in NLP .

First, let's see the types of ambiguity, and then see how to handle them by using the means that are available. Refer to Figure 3.13 for the different types of ambiguity: