User talk:BIBEK NLP

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Bengali Verb
In Bangla Verb plays a very important role. Translation of a bangle sentence to another sentence may change depending on the sense variation for a specific verb V1 for presence of word Wi. For a bangla Verb (V1= khaai) and words (Wi = {“bhaat”, “jal”, “sigaareT”}) translation of a sentence S can change. Consider three examples below: 1.	aamraa bhaat (w1) khaai (v1)  We eat rice. 2.	aamraa jal (w2) khaai (v1)  We drink water. 3.	aamraa sigaareT (w3) khaai (v1)  We smoke cigarette. So, to analyze the above sentence we need to apply word knowledge for the above three words (w1,w2,w3) as follows: word	Semantic Meaning	Translation of verb Khaai (v1) bhaat	[SOLID] [edible]	eat jal	[LIQUID]	drink sigaareT	[GAS] [intoxication]	smoke Here sense of verb “khaai” is modified by the nouns “bhaat”, “jal”, “sigaareT”. In Bangla not only sense of verb is modified by the noun, some time sense of noun is also modified by another noun. For example consider the following sentences: 1)	aamaar sigaareTer neeshaa aache  I am intoxicated to cigarette. 2)	aamaar bi-er neeshaa aache I have a passion for reading book. Or I have fascination for books. So, for the same verb “aache”, the noun “neeshaa” give two different sense depending on noun “sigaareT” and “bier”. For noun “sigaareT” the noun “neeshaa” give sense of “intoxication” and for noun “bier” the noun “neeshaa” give sense of “passion” or “habit” or “fascination”. So we need to analyze expectation and valency of words.

In Bangla Sentence verb plays a vital role. From the verb you can identify subject as well as object. Not only identifying the verbs but also it’s morphological information help to analysis of Bengali sentence construction. So, there is a need of collecting Bengali verbs as well as its morphological information. But manually verb collection process needs long time. So, to speed up the process, we programmatically done this job of morphological analysis and morphological synthesis.

We have collected 747 root Bengali Verbs and assigned different paradigm numbers on these verb roots. After collecting the verbs and assigning the paradigm numbers on these verb roots we programmatically generate 50 forms of each verb roots. The exceptional verbforms are generated manually. We also generated nonfinite verb programmatically by adding some suffixes with root verbs. Obiviously after generation there were some error which were manually corrected. These total process we have completed within 3 weak. Then total collected verbs ( both finiteverb ( ~36588) and nonfineverb(~1639)) are filtered form the uniquely colled Bengali word (~2,23,999). After this process we have found 4304 number of verb forms out of 2,23,999 unique words. Then we find out the occurance of each verb in our 3 lakhs Bengali Corpus.

The most important criteria that go into defining a verb: its valency (i.e. the number of basic arguments that it requires) and its case requirements (i.e. the semantic roles played by the basic arguments). When combined, the valency and case requirements of a verb are usually referred to as the argument structure of the verb.

Let us know about valency and case. Consider the example below:

baandarti paathar diye janlati bhaanglo (Bangla sentence) The monkey broke the window with stone. (English Sentence)

In this example the verb “bhaanglo” (past form of root verb “bhaang”) has a valency two, since it require two arguments: the subject “baandati” and the object “janlati”. The arguments are requiring because if missing of one argument can not express the meaning of the sentence properly (baandarti bhaanglo object missing, janlati bhaanglo  subject missing). In Bangla many time subject or object or verb are missing in a sentence. So it is very challenging task for analyze the bangla sentence. The three major case roles that are capable of being included within the valency of a verb are: agent - the entity responsible for the event described by the verb

patient - the entity which experiences the state or change of state described by the verb

focus - the entity which acts as the referent of a relationship with the patient Thus, the agent is responsible for the event, the patient experiences the event, and the focus provides the referent for the state or change of state indicated by the event.

License tagging for Image:Benagali to hindi.pdf
Thanks for uploading Image:Benagali to hindi.pdf. Wikipedia gets thousands of images uploaded every day, and in order to verify that the images can be legally used on Wikipedia, the source and copyright status must be indicated. Images need to have an image tag applied to the image description page indicating the copyright status of the image. This uniform and easy-to-understand method of indicating the license status allows potential re-users of the images to know what they are allowed to do with the images.

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This is an automated notice by OrphanBot. If you need help on selecting a tag to use, or in adding the tag to the image description, feel free to post a message at Media copyright questions. 11:04, 21 December 2006 (UTC)

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