It means you want me to write small story integrating these entities.?

On Tue, Jun 24, 2014 at 5:59 PM, Mark G <[email protected]> wrote:

> Hello, you need to annotate the entity within some of the sentences it
> occurs in. The name finder needs context. It's giving you the same sentence
> back because it was trained to find any token anywhere.
> Mg
>
>
> > On Jun 24, 2014, at 8:12 AM, Vivekanand Ittigi <[email protected]>
> wrote:
> >
> > Hi Jorn,
> >
> > Let me use training model itself.
> >
> > Let me just say what i've done so far
> >
> > 1. I've written the following text into a file called test.train
> > <START:Product_entities>icm2500<END>
> > <START:Product_entities>prd_234<END>
> > .
> > .
> > .
> >
> > 2.  i ran the following
> >
> > ./opennlp TokenNameFinderTrainer -encoding UTF-8 -lang en -data
> test.train
> > -model en-ner-person.bin
> >
> > 3. I've added the bellow line in "sometext.txt"
> >
> > What is the risk value on icm2500. Delivery of prd_234 will be arrived
> > late. Watson is handling router_34.
> >
> > 4. I ran the command
> >
> > ./opennlp TokenNameFinder en-ner-person.bin <sometext.txt>
> > output/output4.txt
> >
> > result: It threw me the same line instead of What is the risk value on
> > <START:Product_entities>icm2500<END> Delivery of
> > <START:Product_entities>prd_234<END> will be arrived late.......
> >
> > Please tell me what am i doing wrong??????
> >
> > Thanks,
> > Vivek
> >
> >
> >
> >
> >
> >> On Tue, Jun 24, 2014 at 5:06 PM, Jörn Kottmann <[email protected]>
> wrote:
> >>
> >>> On 06/24/2014 01:10 PM, Vivekanand Ittigi wrote:
> >>>
> >>> Hi Jorn,
> >>>
> >>> I read the document
> >>> http://opennlp.apache.org/documentation/manual/opennlp.
> >>> html#tools.namefind.recognition.cmdline.
> >>> But i felt i needed more information to put it in code.
> >>>
> >>> I got to know that we need to train the model. But could not get it.
> >>> Can you please explain it. so that i could start implementing it.
> >>>
> >>> Thanks,
> >>> Vivek
> >>>
> >>> Thanks,
> >>> Vivek
> >>>
> >>>
> >>> On Tue, Jun 24, 2014 at 3:28 PM, Jörn Kottmann <[email protected]>
> >>> wrote:
> >>>
> >>>> On 06/24/2014 09:44 AM, Vivekanand Ittigi wrote:
> >>>>
> >>>> Hi,
> >>>>>
> >>>>> If i use a query like this in command line
> >>>>>
> >>>>> ./opennlp TokenNameFinder en-ner-person.bin <input.txt> <output.txt>
> >>>>>
> >>>>> I'll get person names printed in output.txt but I want to write own
> >>>>> models
> >>>>> such that i should print my own entities.
> >>>>>
> >>>>> E.g.
> >>>>>
> >>>>> 1. what is the risk value on icm2500.
> >>>>> 2. Delivery of prd_234 will be arrived late.
> >>>>> 3. Watson is handling router_34.
> >>>>>
> >>>>> If i pass these lines, it should parse and extract product_entities.
> >>>>> icm2500, prd_234, router_34... etc these are all Products( we can
> save
> >>>>> this
> >>>>> information in a file and we can use it as look up kind of for
> models or
> >>>>> openNLP).
> >>>>>
> >>>>> Can anyone please tel me how to do this  ?
> >>>>>
> >>>>>
> >>>>> You need to train your own model. To do that you have to collect some
> >>>> of
> >>>> the texts
> >>>> and annotate them with the entities you wish to detect.
> >>>>
> >>>> Have a look at the documentation about the name finder. It explains
> how
> >>>> to
> >>>> the training
> >>>> works.
> >> For the training you need to produce annotated texts like the sample in
> >> the documentation.
> >> If you have a training data file in that format you can use the command
> >> line interface to
> >> actual train a model.
> >>
> >> The latest trunk version of OpenNLP can also be trained on files in the
> >> brat data format,
> >> those can be easily created with brat.
> >>
> >> Have a look here:
> >> http://brat.nlplab.org/index.html
> >>
> >> In my experience brat works quite well in the latest trunk version.
> >>
> >> To train with brat you need to suffix the training command like this
> >> bin/opennlp TokenNameFinderTrainer.brat
> >> That command will print a help message explaining the inputs it needs.
> >>
> >> There is no need to write code to train a name finder model.
> >>
> >> Jörn
> >>
> >>
> >>
> >>
> >>
>

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