README

NAME
    NLP::Service

SYNOPSIS
    NLP::Service is a RESTful web service based off Dancer to provide
    natural language parsing for English.

VERSION
    0.02

METHODS
    run()
        The "run()" function starts up the NLP::Service, and listens to
        requests. It currently takes no parameters. It makes sure that the
        NLP Engines that are being used are loaded up before the web service
        is ready.

        It takes a hash as an argument with the following keys:

        force   Forces the loading of all NLP models before doing anything.
                The value expected is anything that is not 0 or undef, to be
                able to do this. Example,

                "NLP::Service::run(force => 1);"

        config  Takes in a configuration for the internal service
                implementation. Currently the implementation is using
                Dancer, and all of these keys correspond to Dancer::Config.
                For more details, refer to Dancer config for the acceptable
                values. Example,

                "NLP::Service::run(config => { logger => 'console' });"

    load_models()
        The "load_models()" function creates all the required NLP models
        that are supported. This is internally called by the "run()"
        function, so the user does not explicitly need to call them. It is
        useful however, for explicit loading of the models, if the models
        need to be used in unit tests or elsewhere.

        In void context it returns nothing, but in scalar context returns
        the number of models that were loaded, and in list context returns a
        hash with the keys being model names and the values being the actual
        references to the perl objects that represent the models. This is
        rarely necessary for the user to be using.

        It takes a single argument which is a boolean to forcibly load the
        parsers or not. By default the lazy load option is assumed unless
        explicitly set by the user. For example,
        NLP::Service::load_models(1) for forced loading and
        "NLP::Service::load_models()" for lazy loading.

RESTful API
    Multiple formats are supported in the API. Most notably they are XML,
    YAML and JSON. The URIs need to end with ".xml", ".yml" and ".json" for
    XML, YAML and JSON, respectively.

    GET */nlp/models.(json|xml|yml)*
        Returns an array of loaded models. These are the model names that
        will be used in the other RESTful API URI strings.

    GET */nlp/languages.(json|xml|yml)*
        Returns an array of supported languages. Default is "en" for
        English.

    GET */nlp/info.(json|xml|yml)*
        Returns a hashref of details about the NLP tool being used.

    GET/POST */nlp/relations.(json|xml|yml)*
        The user can get a list of all the english grammatical relations
        supported by the NLP backend.

    GET/POST */nlp/parse/$model.(json|xml|yml)*
        The user can make GET or POST requests to the above URI constructed
        by the user or their programs. The $model corresponds to one of the
        available models such as "en_pcfg", "en_factored", etc. The list of
        supported models are returned by the GET request to
        "/nlp/models.(json|xml|yml)" URI.

        The return value is a Part of Speech tagged variation of the input
        parameter *data*.

        The parameters needed are as follows:

        data
          One of the parameters expected is *data* which should contain the
          text that needs to be parsed and whose NLP formation of
          Part-of-Speech tagging needs to be returned.

    GET/POST */nlp/parse.(json|xml|yml)*
        This performs the same function as above, but picks the default
        model which is "en_pcfg". It expects the same parameters as above.

COPYRIGHT
    Copyright (C) 2011. Vikas Naresh Kumar <vikas@cpan.org>

    This is free software; you can redistribute it and/or modify it under
    the same terms as the Perl 5 programming language system itself.

    Started on 25th March 2011.