The study of Natural Language Processing(NLP) started somewhere in the 1950s. Ever since there has been a lot of advancement in this field. It has been into a cycle of regular evolution which has caused it to be a very powerful weapon in the world of Artificial Intelligence.
Despite so much of achievement so far, there are still a lot of limitations/Problems NLP has. Natural Language Understanding is one of the areas in which NLP is lagging behind the most. Despite so much of advancement, there is no NLP model that can excel like human beings. Today, In this post, we are going to discuss some of them.
1. Ambiguity :
One of the biggest challenges is to understand the meaning of an Ambiguous statement(statement open to different interpretations). NLP may a times do not handle Ambiguous statement nicely.
For eg: "John went to the bank", here the word 'bank' an either refer to where the money is kept or it could be a river bank.
2. Synonymy:
The same ideas can often be constructed into sentences in which one word could be replaced by its synonym without really changing the meaning of the text. But NLP some times fail to understand the fact that in some cases sysnyms can also change the meaning of the whole text.
For eg: 'large' and 'big.' are synoyms. "He is my big brother" cannot be replaced by "He is my Large brother".
3. Intention/Sarcasm :
I am honestly quite skeptical about NLP models understanding the level of sarcasm which is quite common to Humans. It is one of the limitations of NLP. People might sarcastically criticize a product and the Model might interpret in a different way.
4. Language-Resource unavailability:
Even though there are thousands of Languaguages spoken World-wide but there is hardly any data resources available in other languages other than English and Chinese.
So, because of this problem, it might be quite fair to say that NLP is powerful only for Languages like English and Chinese only.
Now, we have come to the end of the article. Feel free to ask any questions in the comment section below.
Despite so much of achievement so far, there are still a lot of limitations/Problems NLP has. Natural Language Understanding is one of the areas in which NLP is lagging behind the most. Despite so much of advancement, there is no NLP model that can excel like human beings. Today, In this post, we are going to discuss some of them.
1. Ambiguity :
One of the biggest challenges is to understand the meaning of an Ambiguous statement(statement open to different interpretations). NLP may a times do not handle Ambiguous statement nicely.
For eg: "John went to the bank", here the word 'bank' an either refer to where the money is kept or it could be a river bank.
2. Synonymy:
The same ideas can often be constructed into sentences in which one word could be replaced by its synonym without really changing the meaning of the text. But NLP some times fail to understand the fact that in some cases sysnyms can also change the meaning of the whole text.
For eg: 'large' and 'big.' are synoyms. "He is my big brother" cannot be replaced by "He is my Large brother".
3. Intention/Sarcasm :
I am honestly quite skeptical about NLP models understanding the level of sarcasm which is quite common to Humans. It is one of the limitations of NLP. People might sarcastically criticize a product and the Model might interpret in a different way.
4. Language-Resource unavailability:
Even though there are thousands of Languaguages spoken World-wide but there is hardly any data resources available in other languages other than English and Chinese.
So, because of this problem, it might be quite fair to say that NLP is powerful only for Languages like English and Chinese only.
Now, we have come to the end of the article. Feel free to ask any questions in the comment section below.
Great work
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