Hi, The very fact that you are trying to answer factoid questions to start with, it is better to use OpenNLP components to identify NER (Named Entity recognition) in the document and use those tags as part of your indexing process.
REgards Vasu On Thu, Mar 5, 2009 at 8:19 PM, Seid Mohammed <seidy...@gmail.com> wrote: > For my work, I have read an article stating that " Answer type can be > automatically constructed by Indexing Different Questions and Answer > types. Later, when an unseen question apears, answer type for this > question will be found with the help of 'similarity function' > computation" > > so I am clear with the arguement above. my problem is, > 1. how can I index individual questions and Answer types as is ( not > tokenized > 2. how can I calculate the similarity between indexed questions and > and unseen questions (question of any type that can be asked latter) > > to make things clear: the senario is > 1. Who is the president of UN > Answer type <Person> > 2. When will the presidency of Meles Zenawi hold? > Answer Type <Date> > these two will be indexed and > and later an unseen question like > who is the president of Kenya > should match the first question and so that will have answer > type of <Person> > > I appricate any help > > Seid M > > --------------------------------------------------------------------- > To unsubscribe, e-mail: java-user-unsubscr...@lucene.apache.org > For additional commands, e-mail: java-user-h...@lucene.apache.org > >
