Skip to content

Latest commit

 

History

History
149 lines (114 loc) · 6.23 KB

README.md

File metadata and controls

149 lines (114 loc) · 6.23 KB
Raw

The Inari Sami morphology and tools

Maturity Lemma count GitHub issues License Doc Build Status CI/CD Build Status

Download nightly / CI/CD installation packages for testing (contains the core zhfst file(s)):

Windows MacOS Mobile

NB!! Note that the nightly / CI/CD installation packages are not tested for language quality, and might contain regressions and errors.

This repository contains finite state source files for the Inari Sami language, for building morphological analysers, proofing tools and dictionaries. The data and implementation are licenced under LICENSE licence, also detailed in the LICENSE. The authors named in the AUTHORS file are available to grant other licencing choices.

Install proofing tools and keyboards for the Inari Sami language by using the Divvun Installer (some languages are only available via the nightly channel).

Download and test speller files

The speller files downloadable at the top of this page (the *.bhfst files) can be used with divvunspell, to test their performance. These files are the exact same ones as installed on users' computers and mobile phones. Desktop and mobile speller files differ from each other in the error model and should be tested separately — thus also two different downloads.

Documentation

Documentation can be found at:

Core dependencies

In order to compile and use Inari Sami language morphology and dictionaries, you need:

To install VislCG3 and HFST, just copy/paste this into your Terminal on macOS:

curl https://apertium.projectjj.com/osx/install-nightly.sh | sudo bash

or terminal on Ubuntu, Debian or Windows Subsystem for Linux:

wget https://apertium.projectjj.com/apt/install-nightly.sh -O - | sudo bash
sudo apt-get install cg3 hfst

or terminal on RedHat, Fedora, CentOS or Windows Subsystem for Linux:

wget https://apertium.projectjj.com/rpm/install-nightly.sh -O - | sudo bash
sudo dnf install cg3 hfst

Alternatively, the Apertium wiki has good instructions on how to install the dependencies for Mac OS X and how to install the dependencies on linux

Further details and dependencies are described on the GiellaLT Getting Started pages.

Downloading

Using Git:

git clone https://github.com/giellalt/lang-smn

Using Subversion:

svn checkout https://github.com/giellalt/lang-smn.git/trunk lang-smn

Building and installation

INSTALL describes the GNU build system in detail, but for most users it is the usual:

./autogen.sh # This will automatically clone or check out other GiellaLT dependencies
./configure
make
(as root) make install

Citing

If you use language data from more than one GiellaLT language, consider citing our LREC 2022 article on whole infra:

Linda Wiechetek, Katri Hiovain-Asikainen, Inga Lill Sigga Mikkelsen, Sjur Moshagen, Flammie Pirinen, Trond Trosterud, and Børre Gaup. 2022. Unmasking the Myth of Effortless Big Data - Making an Open Source Multi-lingual Infrastructure and Building Language Resources from Scratch. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 1167–1177, Marseille, France. European Language Resources Association.

If you use bibtex, following is as it is on ACL anthology:

@inproceedings{wiechetek-etal-2022-unmasking,
    title = "Unmasking the Myth of Effortless Big Data - Making an Open Source
    Multi-lingual Infrastructure and Building Language Resources from Scratch",
    author = "Wiechetek, Linda  and
      Hiovain-Asikainen, Katri  and
      Mikkelsen, Inga Lill Sigga  and
      Moshagen, Sjur  and
      Pirinen, Flammie  and
      Trosterud, Trond  and
      Gaup, B{\o}rre",
    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation
    Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.lrec-1.125",
    pages = "1167--1177"
}