I created classifier to classy the class of nouns,adjectives, Named entities in given sentence. I have used large Wikipedia dataset for classification.
Like :
Where Abraham Lincoln was born?
So classifier will give this short of result - word - class
- Where - question
- Abraham Lincoln - Person, Movie, Book (because classifier find Abraham Lincoln in all there categories)
- born - time
When Titanic was released?
- when - question
- Titanic - Song, movie, Vehicle, Game (Titanic classified in all these categories)
Is there any way to identify exact context for word?
Please see :
- Word sense disambiguation would not help here. Because there might not be near by word in sentence which can help
Lesk algorithm with wordnet or sysnet also does not help. Because it for suppose word
Banklesk algo will behave like this======== TESTING simple_lesk ===========
TESTING simple_lesk() ...
Context: I went to the bank to deposit my money
Sense: Synset('depository_financial_institution.n.01')
Definition: a financial institution that accepts deposits and channels the money into lending activities
TESTING simple_lesk() with POS ...
Context: The river bank was full of dead fishes
Sense: Synset('bank.n.01')
Definition: sloping land (especially the slope beside a body of water)
Here for word bank it suggested as financial institute and slopping land. While in my case I am already getting such prediction like Titanic then it can be movie or game.
I want to know is there any other approach apart from Lesk algo, baseline algo, traditional word sense disambiguation which can help me to identify which class is correct for particular keyword?
Titanic -
when , how long, duration, bornand so on. It's not enough intelligent to identifyreleasedas time based event. Semi superwise and unsuperwised learning system might have identified it - user123