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PHP Natural Language Generation helper classes ============================================== These are pure PHP helper classes to implement recursive-descent natural language generators . The classes provided are an abstract generator, an ontology container and a lexicon container. These classes should help build simple to mid-level generators, speaking about their complexity. Emphasis has been made in keeping more advanced features out of the way for simpler cases (i.e., if there is no need to use the ontology or the lexicon, they can be skipped). The generator keeps track of semantic annotations on the generated text, so as to enable further generation functions to reason about the text. A global context blackboard is also available. This is work in progress, see the ROADMAP for some insights in future development.  http://duboue.net/blog5.html How to use it ============= Look at the examples/ folder, but in a nutshell, subclass the nlg\Generator class and implemented a function named 'top'. This function can return either a string or an array with a 'text' and 'sem' for semantic annotations on the returned text. If you want to use other functions to assemble the text use $this->gen('name_of_the_function', $data_array_input_to_the_function) to call it (instead of $this->name_of_the_function($data_array_input_to_the_function). The generator abstract class keeps track of the semantic annotations for you and other goodies. If the functions that implement the grammar are protected, a dynamic class can be created with the NewSealed class method. This dynamic class will have function interception so you can call $this->name_of_function as usual but actually $this->gen will be called. Either way you use it, to call the class, if your instantiated subclass is $my_gen then $my_gen->generate($input_data_as_an_array) will return the generated strings. If you want to access the semantic annotations, use $my_gen->semantics() afterward. For different use cases, see the examples/ folder. Learning more about NLG ======================= I highly recommend Building Natural Language Generation Systems (2000) by Reiter and Dale. The SIGGEN site  has plenty of good resources. You might also want to look at the NLG portal at the Association for Computational Linguistics wiki . Last but not least, you might be interested in the author's blog  and the class notes of his recent NLG course .  http://www.siggen.org/  http://aclweb.org/aclwiki/index.php?title=Natural_Language_Generation_Portal  http://duboue.net/blog.html  http://wiki.duboue.net/index.php/2011_FaMAF_Intro_to_NLG