# Technical Documentation

## Data
The projects requires additional runtime data to be able to performs its operations. These are the dictionaries in csv format:
- data/lang/es: Spanish dictionaries.
- data/lang/gl: Gallego dictionaries.

- data/lang/gl/abr.txt: Contains a series of abbreviations, along with their expanded form.
- data/lang/gl/acron.txt: Contains a series of acronyms, along with their expanded form.
- data/lang/gl/adxectivos.txt: Contains a series of adjectives, along with their number and gender.
- data/lang/gl/bigramas.dat: Binary data of a 2-gram neural network.
- data/lang/gl/bigramas_real.dat: Binary data of a 2-gram neural network.
- data/lang/gl/clases_ambiguedad.dat: Binary data of a neural network that collapses the grammar category of a word.
- data/lang/gl/derivativos.txt: Contain rules for generating derivative words from certain rules.
- data/lang/gl/desinencias.txt: Contains a series of verb endings.
- data/lang/gl/locucions.txt: Contains a series of verb locucions, along with their grammar category.
- data/lang/gl/nomes.txt: Contains a series nouns, with their number and gender.
- data/lang/gl/palabrasFunction.txt: Dictionary with all the function words.
- data/lang/gl/pentagramas.dat: Binary data of a 5-gram neural network.
- data/lang/gl/pentagramas_real.dat: Binary data of a 5-gram neural network.
- data/lang/gl/perifrase.txt: Dictionary with all the periphrases.
- data/lang/gl/tetragramas.dat: Binary data of a 4-gram neural network.
- data/lang/gl/tetragramas_real.dat: Binary data of a 4-gram neural network.
- data/lang/gl/trigramas.dat: Binary data of a 3-gram neural network.
- data/lang/gl/trigramas.dat: Binary data of a 3-gram neural network.
- data/lang/gl/unigramas.dat: Binary data of a 1-gram neural network.
- data/lang/gl/utf8chars.csv: Contains a series of custom transformation from UTF-8 words to latin1
- data/lang/gl/verbos.txt: Contains all the verbs, along with their roots.

## Classes
- Cotovia: The primary entry point of the application. It handles the loading and unloading of dictionaries and processes sentences. 
- PreprocessorUTF8::Processor: Handles the transformation of strings in UTF-8 into latin1.
- Tokenizar: Manages the tokenization of an input string
- Preproceso: Applies a series of transformations to a tokenized input string to ensure it is in a canonical form. 
- Analisis_morfologico: Applies a morphologic analysis in which it deduces the classification of each token without contextual information. 
- Analisis_morfosintactico: Uses a neural network and an n-gram model to compute the classification of each word.
- Sintagma: Performs syntagma analysis on the input tokens, clustering the tokens into groups.
- Transcripcion: Takes a tokenized sentence and transforms it into multiple phonemes.

## Tests
In the "tests" folder, there is a python script that performs integration tests on the cotovia projects. The following aspects are tested:
- Allomorphs of articles in affirmative sentences with a period  
- Allomorphs of articles in affirmative sentences  
- Allomorphs of articles in exclamatory sentences  
- Allomorphs of articles in interrogative sentences  
- Galician recognition  
- Galician voice  
- Feminine names  
- Masculine names  
- Number recognition  
- Number pronunciation  
- Ordinal numbers  
- Roman numerals  
- Punctuation marks  
- Punctuation marks (variant N)  
- Phonemes