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Word to Concept

An OpenGRM and OpenFST solution for word tagging, Eduard Caizer.

The system

The system is developed entirely in bash, this is the structure:

├── README.md
├── clear.sh
├── init.sh
├── lus.config
├── make.sh
├── originalData
└── scripts
    └── test_word_concept

Installing

The installation is easy, just clone the project and run the following commands:

$ git clone https://github.com/Rezyak/LUS-Project-2.git
$ ./init.sh

this script creates the project structure from the lus.config file

utils	
-	single
-	composed
-	language
transducers
-	transducerModel
-	fsts
-	epss
-	languageModel
data
-	test
-	-	split
-	train
results

as a result of init.sh you will have

├── data
│   ├── test
│   │   └── split
│   └── train
├── originalData
├── results
├── scripts
│   └── test_word_concept
├── transducers
│   ├── epss
│   ├── fsts
│   ├── languageModel
│   └── transducerModel
└── utils
    ├── composed
    ├── language
    └── single

init calls also the create_utils.sh script, this script creates all file used to make the tranduces and calculate the weights

└── utils
    ├── composed
    │   ├── lemmaAndWord_concept
    │   ├── lemma_postag
    │   ├── lemma_words
    │   ├── postag_concept
    │   ├── train_united
    │   ├── word_concept
    │   ├── word_lemma
    │   ├── word_postag
    │   └── word_postag_concept
    ├── language
    │   ├── concept_language
    │   └── postag_language
    └── single
        ├── concept
        ├── lemma
        ├── postag
        └── words

Running

To run the script that make the transducer word to concept with language model run:

$ ./make.sh

it will create a transducer_word_concept and for each sentence in the data/test/split/test_sentences file, it will compose compiled string with the transducer and the language model

Evaluation

at the end of the script run

$ ./scripts/conlleval.pl < results/test_word_concept/to_eval

Cleaning the project

just run

$ ./clean.sh

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