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forked from GitHub/gf-rgl

Wrote a readme guide for folder 'src' and a separate readme for tamil

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Yap Jun Hong (Nemo)
2022-08-14 14:20:03 +08:00
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# Introduction
## Intended audience of this Readme
This Readme is designed for new developers who wish to either extend/improve on a resource grammar or create a new one. It provides an overview of the relationships between files and a simple working pipeline for developers to get started.
Note that while files in this folder are meant to be named with 3 letter suffixes representing the language, e.g. "ResBul" for the Bulgarian resource file, this Readme will use a 4 letter suffix "Lang" to represent a language in general, e.g. "ResLang".
## Author(s) of this Readme
This Readme was written by Nemo and edited by Inari on 14th August 2022.
# Creating a new resource grammar
If you are working on an RGL for a new language, you will need to run "Clone.hs" in the "src" folder so that you can clone a project from another language to your language to give you a basis to start with.
As per the instructions, the syntax is "Clone fromdir todir fromlang tolang", e.g. "runghc Clone swedish danish Swe Dan". You may want to add the option --comment-body after the word "Clone" to comment out every line in the body of the files to start fresh.
This is especially useful if your new language has very little in common with the language you are copying from because they come from different language families.
# File hierarchy
The number of files may be overwhelming, but they are related together following the graphic under "Module dependencies" under the rgl-tutorial. In the graphic, an example is that GrammarIta and ResIta are dependent on Prelude as they have arrows pointing towards the Prelude ellipse.
http://www.grammaticalframework.org/lib/doc/rgl-tutorial/index.html
The below graphic is an alternative graphic explaining the relations, taken from private correspondence with Inari.
Lang
/ \
Lexicon Grammar
/ | | | \
Adjective Adverb Noun Verb Phrase …
\ | | | | | | | | | | | | | | /
Cat
CatLang defines the categories, and the modules AdjectiveLang, NounLang, SentenceLang, PhraseLang, and so on, all extend Cat. The Grammar is defined as a collection of all those AdjectiveLang, NounLang, SentenceLang, and so on modules. LangLang is defined as the collection GrammarLang and LexiconLang and is where you will be checking your program. You may ignore:
- AllLangAbs, AllLang, ExtendLang, ExtraLangAbs, ExtraLang, ConstructionLang, DocumentationLang, MarkupLang, BackwardLang
If the language you cloned from has any of these resource modules, you can remove them completely:
- IrregLang (unless you want to populate it with irregular verbs of your own language), MissingLang (see how to generate your own if you need it later: https://inariksit.github.io/gf/2018/08/28/gf-gotchas.html#generating-missingxxx)
# Relationships between functions in files
There may be several ways the functions within the files are organised relative to one another. In other words, there may be several schemas depending on the author. More recent RGLs might implement one schema detailed by this blog post by Inari.
https://inariksit.github.io/gf/2018/08/28/gf-gotchas.html#my-naming-scheme-for-lincats-and-opers
# Main goal
You may think of your long-term goal as eventually implementing all the abstract functions found in the "abstract" folder. In other words, you are somewhat constrained by the available categories in Cat.gf and functions in relevant e.g. Noun.gf, Verb.gf etc. files.
In the future, if you find that the available functions do not apply to your language, you may search in the Extend.gf file for more optional functions, or in Extra.gf. if it doesn't exist, create your own ExtraLangAbs.gf with the concrete ExtraLang.gf, all in the same directory gf-rgl/src/lang. This blog post contains more information.
https://inariksit.github.io/gf/2021/02/15/rgl-api-core-extensions.html#language-specific-extra-modules
There is a prioritised list of RGL functions for new resource grammars written by contributor heatherleaf. You can start by implementing the "+++" functions.
https://github.com/GrammaticalFramework/gf-rgl/issues/238
# Working pipeline example
For a pipeline, You might wish to start with implementing functions that create Noun Phrase like DetCN: Det -> CN -> NP; a function that takes a Determiner and a Common Noun and gives a Noun Phrase. In this case, the workflow is done by editing:
1. ResLang: Contains the relevant Operations (Opers) for e.g. "Noun", "mkN", "Determiner" and "Quant".
2. ParamLang: Contains the language paramters used in ResLang.
3. CatLang: CatLang will be defined in terms of Opers found in ResLang. This means that instead of Defining NP in CatLang as, say, {s: Str}, you will define NP as ResLang.NounPhrase, which points to a NounPhrase Oper in ResLang. Then you need to implement the word syntax in NounLang.
4. NounLang: Contains the relevant lins in defining sentence structure.
5. LexiconLang: Contains the lins that define the Noun words.
As you will have to define a determiner that is created from a Quant, you will have to look at the following files too.
6. StructuralLang: Contains the lins that define the Quant/Determiner words.
Note that you will have to use mkQuant instead of creating Det by mkDet directly.
# Testing your work
When you are done with your implementation, you may test that everything works by starting up LangLang and, in this case, writing something like:
```DetCN (DetQuant xxxx_Quant NumSg) (UseN xxxx_N)```
Where you replace 'xxxx' with the word in Lang.

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# Tamil
## Language info
- English name: Tamil
- Autonym: Tam
- ISO code: Tam
## History
This tamil resource grammar library was started on 13th August 2022. It was copied from the Malay resource grammar library with all bodies commented out.
## Author(s)
Created and maintained by Nemo, 2022
## Publications
None
## Implementation information
### 13th August 2022
A conjugation table for verbs and an inference table for nouns have been implemented. A basic DetCN function taking a determiner and a common noun to combine to a noun phrase has also been implemented, with one determiner ("this_Quant") and one noun ("house_N") in use. Use the command "gr -cat=NP" to generate the tree.