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This page pertains to UD version 2.

Release checklist

This checklist is meant to provide guidance for teams contributing treebank data for a new release of Universal Dependencies. It was created for release v1.2 and applies, unless otherwise noted, to any upcoming release.

Contents:

Executive summary

Repository and files

Every language has its own GitHub repository called UD_Language, where Language is the name of the language. For example, the repository for Finnish is called UD_Finnish. Make sure to create the repository for your language if it does not already exist. Some languages have more than one treebank and the additional treebanks have their own repositories with a -Treebank identifier after the language name. For example, UD_Finnish-FTB is the repository for the FinnTreeBank, while the plain UD_Finnish holds the Turku Dependency Treebank.

Every language repository should contain the following five files (where xx is the ISO code for the given language; if this is not the first treebank for the language, use xx_y instead, where y is the lowercased treebank identifier):

  1. xx-ud-train.conllu
  2. xx-ud-dev.conllu
  3. xx-ud-test.conllu temporary rule for UD 2.0: do not publish the test set! Validate it offline and then send it by e-mail to ud.conll.shared.task.2017@gmail.com.
  4. README.txt or README.md
  5. LICENSE.txt

The first three files contain the treebank data split into a training, development and test set. These should be in CONLL-U format and conform to the universal guidelines. They need to be validated as described below.

If the treebank consists of more than 20,000 words, make the test set and dev set at least 10,000 words each, even if it leaves you with training data smaller than development data (that is necessary for the CoNLL 2017 shared task). There is no upper limit on the size of dev/test. If you cannot reach 10,000 words of test data, use a more typical split, e.g. 80-10-10% (but the treebank will not be included in the shared task).

The training-development-test data split should be stable across releases. It should not happen that a sentence that was once part of training data ever appears in the test data, and vice versa (except for sentences that are naturally occurring duplicates in independent texts). We want to prevent accidental misguided results of experiments where people take a parser trained on UD 1.1 and apply it to test data from UD 1.2. We decided to make an exception to this rule for UD 2.0 where it is needed to achieve 10K test or dev, on the ground that v2 annotation is not backward-compatible anyway.

The README.txt file contains basic documentation of the treebank and machine-readable metadata for the UD main page (see below) and the LICENSE.txt specifies under what license the treebank is made available.

Repositories of released treebanks also contain a stats.xml file, which is generated as part of the release-building process, using the script conllu-stats.pl available from the tools repository. Data providers do not have to care about this file.

The README file

The README file is distributed together with the data and summarizes information about the treebank for its users; the contents of the file is also displayed by Github when readers land on the Github homepage of the treebank repository. At the same time, certain pre-defined parts of the README file are automatically copied to the UD website to places where individual treebanks are described. In these cases, the contents is interpreted as MarkDown and you can use the MarkDown syntax to add a little formatting (but please remember that some users will read directly the README file, so it should stay reasonably human-readable). The last part of the README file contains machine-readable metadata (described below) where selected vital information must be provided in a fixed pre-defined way.

MarkDown source files usually have the .md extension (README.md); but for historical reasons, it is also possible to name the file README.txt.

The README file should minimally contain the following information:

  1. A description of the treebank and its origin (creation method, data sources, etc.)
  2. A description of how the data was split into training, development and test sets
  3. If there are multiple genres/domains, can they be told apart by sentence ids? Does the treebank consist of complete documents, or just randomly shuffled sentences?
  4. Acknowledgments and references that should be cited when using the treebank
  5. A changelog section for treebanks that will be released for the second (or subsequent) time
  6. A machine-readable section with treebank metadata. This is described below.

MarkDown uses the # character to mark section headings. Several sections with fixed names are expected in every README and will be searched for by various scripts. Use the following template (from Swedish) to adjust your README. The first section, called Summary, should be rather short (one-two lines), so it can appear in an index page listing all treebanks. An automatically generated treebank page in the UD documentation will take over the sections Summary, Introduction and Acknowledgments.

# Summary

UD Swedish-TP is a conversion of the Prose section of Talbanken, originally annotated in the MAMBA annotation scheme,
and consisting of a variety of informative text genres, including textbooks, information brochures and newspaper articles. 

# Introduction

UD Swedish-TP is a conversion of the Prose section of Talbanken (Einarsson, 1976), originally annotated…

# Acknowledgments 

The new conversion has been performed by Joakim Nivre and Aaron Smith at Uppsala University. We thank everyone who…

# (possibly any number of extra sections)

…

# Changelog

* 2015-05-15 v1.1
  * Added lemmas
  * Corrected tokenization in sentences 123 and 456
* 2015-01-15 v1.0
  * First release in UD

=== Machine-readable metadata (DO NOT REMOVE!) ================================
(described in more detail below)

Treebank metadata

The table on the front page is automatically generated from special lines (metadata) in the README.txt or README.md file for every treebank. The metadata are used for various other automated tasks as well, for example the list of contributors to every UD release is collected from the READMEs.

The metadata describe individual treebanks and there are often multiple treebanks per language. If we want to work on UD documentation for a new language without having actual data, we still must create a Github repository for the future treebank, and fill in the metadata so that the language appears on the front page. The names of the contributors to the documentation should be listed among the treebank contributors, otherwise they will not be included in the overall UD list of contributors.

Here is an example of the treebank metadata block from the Czech README file

=== Machine-readable metadata (DO NOT REMOVE!) ================================
Data available since: UD v1.0
License: CC BY-NC-SA 3.0
Includes text: yes
Genre: news
Lemmas: converted from manual
UPOS: converted from manual
XPOS: manual native
Features: converted from manual
Relations: converted from manual
Contributors: Zeman, Daniel; Hajič, Jan
Contributing: elsewhere
Contact: zeman@ufal.mff.cuni.cz
===============================================================================

This block should be the last thing in the README file. The properties are as follows:

If you want to see what web content will be generated from your README file, run the generate_treebank_hub.pl script from the tools repository on your treebank folder, e.g.

tools/generate_treebank_hub.pl UD_Czech > for_web.md

Repository branches

While the official UD release is always through Lindat, many users of UD source their data from the GitHub language repositories. Therefore, the master branch of every language should contain the last, officially released version of the data for the given language. The development in between releases should happen on the dev branch of the repository. Although it is currently not locked, treebank maintainers should never touch the master branch, they should always push to dev. At release time, the release task force will take care of merging the contents of the dev branch into master. Please do not submit pull requests from the dev branch (or from anywhere else) to the master branch. This is not needed for the release merge to take place, and if someone overlooks the destination branch and accepts the pull request, it will again result in a commit to the master branch at wrong time.

(To make things a bit more confusing, this policy of data repositories does not apply to some other repositories that we use. In the docs repository you must work with the pages-source branch. That is done automatically if you edit the documentation in your browser via the edit page link. You will also need to access the tools repository and upload the deprel and feat_val files specific for your treebank. In this case, please use the master branch.)

If you have no previous experience with Git, here is a quick tutorial on how to deal with the branches. Please refer to on-line documentation of Git and Github for more details. The tutorial assumes that you are communicating with Github from a Linux shell. The interface may be different if your OS is Windows. If you are working only with the Github web interface, you are not dependent on your operating system but you must remember to switch the Branch: master drop-down menu (left-hand side of the page) to Branch: dev; it always starts in master by default. In contrast, when you want to clone the repository to your local system, you need the address that is hidden under Clone or download in the right-hand side of the page, and that address is common for all branches. Our example is the Italian repository. Here is how you clone the repo to your system (git clone is the command, the remainder is the address copied from the Github web):

git clone git@github.com:UniversalDependencies/UD_Italian.git
Cloning into 'UD_Italian'...
remote: Counting objects: 215, done.
remote: Total 215 (delta 0), reused 0 (delta 0), pack-reused 215
Receiving objects: 100% (215/215), 6.98 MiB | 4.55 MiB/s, done.
Resolving deltas: 100% (134/134), done.
Checking connectivity... done.

Then enter the cloned folder and switch to (“checkout”) the dev branch. Your copy of the repository knows that such a branch exists on the server but it only creates your local copy of that branch once you ask for it. You may subsequently want to call git pull to make sure that you have the latest contents of the dev branch from the server:

cd UD_Italian
git checkout dev
Branch dev set up to track remote branch dev from origin.
Switched to a new branch 'dev'
git branch
* dev
master
git pull
Already up-to-date.

Once you do this, you are all set. Your copy will stay switched to the dev branch unless you call git checkout master (or other git checkout) again. You will probably mostly need just git status, git diff, git add, git commit, git push and git pull commands. All pushes and pulls will be done against the remote dev branch.

Validation

Data format and repository

Up-to-date automatic validation runs of the repositories are available here. These are based on the dev branch of the data and use the validate.py script described below.

The final data validation is an important step and each file released in the project is expected to validate as conforming to the basic requirements on the data and format. For this purpose, there is a validation script in the tools repository.

$ git clone git@github.com:UniversalDependencies/tools.git
$ cd tools
$ python validate.py -h

In general, you validate the data like so:

python validate.py --lang=xx [file.conllu]

for example for Finnish:

$ python validate.py --lang=fi ../UD_Finnish/fi-ud-dev.conllu
*** PASSED ***

Among other items, the script also validates the language-specific set of tags and relations and therefore it needs to know about these. The language-specific lists are stored in data/deprel.xx (language-specific relations) and data/feat_val.xx (language-specific features). In addition data/*.ud stores the UD taglists. Before you can validate data for a given language, you need to produce and commit the necessary tag lists. You can make the initial lists like so:

$ python conllu-stats.py --deprels=langspec path_to_your_data/*.conllu > data/deprel.xx
$ python conllu-stats.py --catvals=langspec path_to_your_data/*.conllu > data/feat_val.xx

This will gather the language-specific lists in descending order by their frequency. It is important to check the resulting files for correctness, because otherwise the validation would of course be a no-op. Once you have checked the lists manually, you can add them to the repository:

$ git add data/deprel.xx data/feat_val.xx
$ git commit -m "Adding language-specific data for xx."
$ git push

Since the v2.0 release, whitespace is allowed in the FORM and LEMMA fields under conditions specified in here. This is supported in the validator through the UD-wide file data/tokens_w_space.ud and its language-specific variants data/tokens_w_space.xx. In these files, each line is a Python regular expression defining the permissible forms and lemmas that can contain a whitespace.

Syntax

For the v1.3 release, we have created an additional number of tests which try to uncover possible logical inconsistencies in the treebank data. Automatic validation runs for this syntax validation are available here. Unlike the data format and repository validation, this validation machinery is not streamlined enough to be distributed for offline use, therefore it is important to regularly push your data to the dev branch of the repository.

The tests are specified in the file gen_index/stests.yaml and rely on the query language of the SETS search interface.

Language-specific guidelines

Every treebank should be accompanied by a set of language-specific guidelines at http://universaldependencies.org/. These guidelines should minimally specify the following:

  1. Tokenization: How was word segmentation performed? Does the treebank include multiword tokens?
  2. POS tags: What universal POS tags (if any) are not used?
  3. Features: What universal features are not used? What language-specific features/values have been added?
  4. Relations: What universal relations are not used? What language-specific subtypes have been added?

There are more detailed guidelines for language-specific documentation. Also see the general guidelines about how to contribute (which covers the conventions used in writing UD documentation, such as how to format examples).

Building the release

Documentation of the steps to be taken by the release task force is on a separate page.