You can also detect the Parts of Speech of a given sentence and print them with the help of openNlp. You can use short forms of speech than using the full name of the parts of speech. The following table indicates the various parts of speeches detected by OpenNLP and their meanings.
|Parts of Speech||Meaning of parts of speech|
|NN||Noun, singular or mass|
|VB||Verb, base form|
|VBD||Verb, past tense|
|VBZ||Verb, third person singular present|
|IN||Preposition or subordinating conjunction|
|NNP||Proper noun, singular|
If you want to tag the parts of speech of a sentence, use a model with a file named en-posmaxent.bin. This is also known as a predefined model used to train to tag the parts of speech of the given raw text.
The POSTaggerME class of the opennlp.tools.postag package is mainly used to load this model and tag the parts of speech of the given raw text using OpenNLP library. To do so, you need to −
Here are some important steps to be followed to write a program to tag the parts of the speech in the given raw text using the POSTaggerME class.
Here this model for POS tagging is marked by the class named POSModel, which belongs to the package opennlp.tools.postag.
To load a tokenizer model −
The POSTaggerME class of the package opennlp.tools.postag is mainly used to estimate the parts of speech of the given raw text. You can use maximum Entropy to make its decisions.
Following step shows the class and pass the model object created in the previous step.
The tokenize() method of the whitespaceTokenizer class is mainly created to tokenize the raw text passed to it. This method follows a string variable as a parameter, and returns an array of Strings (tokens).
Instantiate the whitespaceTokenizer class and the invoke this method by passing the String format of the sentence to this method.
To generate the tag() method of the whitespaceTokenizer class provides POS tags to the sentence of tokens. This method easily accepts an array of tokens (String) as a parameter and returns tag (array).
While,iInvoke the tag() method by passing the tokens create in the previous step to it.
The POSSample class presents the POS-tagged sentence. To apply this class, we need to have an array of tokens (of the text) and an array of tags.
The toString() method of this class takes back the tagged sentence. Instantiate this class by creating the token and the tag arrays created in the previous steps and invoke its toString()method, as mentioned in the below code.
Below mentioned program tags the parts of speech in the mentioned raw text. Let’s save this program in a file with the name PosTaggerExample.java.
Let’s compile and execute the saved Java file from the Command prompt with the help of below commands –
Once you execute the above code reads the given text and detects the parts of speech of these sentences and displays them, as mentioned below.
Let’s see the below program to tag the parts of speech of a given raw text. It also checks the performance and displays the performance of the tagger. Save this program in a file with the name PosTagger_Performance.java.
Now compile and execute the saved Java file from the Command prompt with below commands –
Once you execute the above code it reads the given text and tags the parts of speech of these sentences and displays them. Along with this it also monitors the performance of the POS tagger and displays it.
The probs() method of the POSTaggerME class is mainly used to find the probabilities for each tag of the recently tagged sentence.
Below mentioned program displays the probabilities for each tag of the last tagged sentence. Now save this program in a file with the name PosTaggerProbs.java.
Let’s compile and execute the saved Java file from the Command prompt with below commands –
Once you execute the above code reads the given raw text, tags the parts of speech of each token in it, and displays them. Along with the its provides the probabilities for each parts of speech in the given sentence, as mentioned below.
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