Hello, The best thing to do would be to manually annotate some data of the same type you want to analyze. In this case, you will be annotating "loan", "insurance" and so on. Then you can train a model to recognize such sequences.
http://opennlp.apache.org/documentation/1.5.3/manual/opennlp.html#tools.namefind If you have only a limited list of words you want to find you could get away with lookups, but for open-ended terms recognition of those types you will need to try to generate training data. Brat is a nice tool to do such annotation http://brat.nlplab.org/ HTH, R On Thu, May 14, 2015 at 8:37 AM, Vashishth, Rahul <[email protected]> wrote: > Hi, > My requirement is to analyze sentence like. "What is health insurence." or > "What is mortgage loan." > For this i need to create a custom models to find the business words in given > array of tokens. So that later on > i can create a query based on given sentence. > As we have models created for person name location name, I need to have a > model for business terms i.e. Loan, Insurance, and > User action i.e. Download, define and English grammar i.e. What, How. > Please let me know how i can achieve this or if there is any other way to > analyze the sentence like that. > > Many Regards, > Rahul Vashishth > > This e-mail, including attachments, may include confidential and/or > proprietary information, and may be used only by the person or entity > to which it is addressed. If the reader of this e-mail is not the intended > recipient or his or her authorized agent, the reader is hereby notified > that any dissemination, distribution or copying of this e-mail is > prohibited. If you have received this e-mail in error, please notify the > sender by replying to this message and delete this e-mail immediately.
