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  • THEaiTRobot 2.0

    The THEaiTRobot 2.0 tool allows the user to interactively generate scripts for individual theatre play scenes. The previous version of the tool (http://hdl.handle.net/11234/1-3507) was based on GPT-2 XL generative language model, using the model without any fine-tuning, as we found that with a prompt formatted as a part of a theatre play script, the model usually generates continuation that retains the format. The current version also uses vanilla GPT-2 by default, but can also instead use a GPT-2 medium model fine-tuned on theatre play scripts (as well as film and TV series scripts). Apart from the basic "flat" generation using a theatrical starting prompt and the script model, the tool also features a second, hierarchical variant, where in the first step, a play synopsis is generated from its title using a synopsis model (GPT-2 medium fine-tuned on synopses of theatre plays, as well as film, TV series and book synopses). The synopsis is then used as input for the second stage, which uses the script model. The choice of models to use is done by setting the MODEL variable in start_server.sh and start_syn_server.sh THEaiTRobot 2.0 was used to generate the second THEaiTRE play, "Permeation/Prostoupení".

  • MSTperl parser (2015-05-19)

    MSTperl is a Perl reimplementation of the MST parser of Ryan McDonald (http://www.seas.upenn.edu/~strctlrn/MSTParser/MSTParser.html). MST parser (Maximum Spanning Tree parser) is a state-of-the-art natural language dependency parser -- a tool that takes a sentence and returns its dependency tree. In MSTperl, only some functionality was implemented; the limitations include the following: the parser is a non-projective one, curently with no possibility of enforcing the requirement of projectivity of the parse trees; only first-order features are supported, i.e. no second-order or third-order features are possible; the implementation of MIRA is that of a single-best MIRA, with a closed-form update instead of using quadratic programming. On the other hand, the parser supports several advanced features: parallel features, i.e. enriching the parser input with word-aligned sentence in other language; adding large-scale information, i.e. the feature set enriched with features corresponding to pointwise mutual information of word pairs in a large corpus (CzEng); weighted/unweighted parser model interpolation; combination of several instances of the MSTperl parser (through MST algorithm); combination of several existing parses from any parsers (through MST algorithm). The MSTperl parser is tuned for parsing Czech. Trained models are available for Czech, English and German. We can train the parser for other languages on demand, or you can train it yourself -- the guidelines are part of the documentation. The parser, together with detailed documentation, is avalable on CPAN (http://search.cpan.org/~rur/Treex-Parser-MSTperl/).

  • THEaiTRobot 1.0

    The THEaiTRobot 1.0 tool allows the user to interactively generate scripts for individual theatre play scenes. The tool is based on GPT-2 XL generative language model, using the model without any fine-tuning, as we found that with a prompt formatted as a part of a theatre play script, the model usually generates continuation that retains the format. We encountered numerous problems when generating the script in this way. We managed to tackle some of the problems with various adjustments, but some of them remain to be solved in a future version. THEaiTRobot 1.0 was used to generate the first THEaiTRE play, "AI: Když robot píše hru" ("AI: When a robot writes a play").

  • Prep for Adventure: A game for the acquisition of English prepositions

    The presented game is designed to teach the six most frequent English prepositions (to, of, in, for, on, and with) at the A1 to A2 levels of proficiency. Prep for Adventure is a single-player game comprised of five separate tasks – jumping puzzle, cooking, town maze, lighting the goblets, and a banter with a classmate. Their mechanics are then combined in the final task (The Final Fight) to elicit the correct responses of the subject. The language used in the game is adjusted for the subjects’ level of proficiency, the game is fully voiced and offers a degree of customization. All tasks are based on the gap-filling type of exercise where subjects have to complete a sentence with a missing word, either by typing it in or via different kinds of multiple-choice formats. The game is designed to advance the subjects’ performance in prepositional structures by exposing players to as much input as possible. The length of one average playthrough is approximately 30-45 minutes. The game was created in the RPG Maker MV engine where RPG stands for role-playing game, which is a genre of a game in which the player adopts a role/roles of a fictional character/characters in a (partly or fully) invented setting. The game story: The Grammar School of Witchcraft has been taken over by the Evil Preposition Magician and the player is trying to win their school back alongside with a young witch named Morphologina (the player’s guide).

  • WordnetLoom 1.68.2

    WordnetLoom – is an wordnet editor application built for the needs of the construction of a the largest Polish wordnet called plWordNet. WordnetLoom provides two means of interaction: a form-based, implemented initially, and a visual, graph-based introduced recently. The visual, graph-based interactive presentation of the wordnet structure enables browsing and its direct editing on the structure of lexico-semantic relations and synsets. WordnetLooms works in a distributed environment, i.e. several linguists can work simulanuously from different sites on the same central database.

  • VU University Diachronic News text Corpus

    The diachronic corpus has been brought in line with current standards and formats as used in the STEVIN Nederlandstalig Referentiecorpus (SoNaR, under development), which has been adapted to the more general FoLiA format (documented by Van Gompel, 2012). These standards and formats have been extended with new layers of annotation. As a result the corpus adheres to the current day CLARIN infrastructure.

  • OpenSONAR: a 500 MW reference corpus of Contemporary Written Dutch

    SoNaR is a 500-million-word reference corpus of contemporary written Dutch for use in different types of linguistic (incl. lexicographic) and HLT research and the development of applications. The STEVIN funded SoNaR project (2008-2011) built on the results obtained in the D-Coi and Corea projects which were awarded funding in the first call of proposals within the STEVIN programme. SONAR contains over 500 million words (i.e. word tokens) of full texts from a wide variety of text types including both texts from conventional media and texts from the new media. All texts except for texts from the social media (Twitter, Chat, SMS) have been tokenized, tagged for part of speech and lemmatized, while in the same set the Named Entities have been labelled. All annotations were produced automatically, no manual verification took place. The texts are enriched with several annotations (Part of Speech and lemma information) and are available as FoLiA xml files (folia.xml). The system relies on BlackLab server as back-end and WhiteLab as user-interface. OpenSONAR is an online application for exploration of and searching in the SoNaR corpus.
    van de Camp, M, Reynaert,MandOostdijk, N. 2017.WhiteLab 2.0: AWeb Interface for Corpus Exploitation. In: Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 231–243. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.19. License: CC-BY 4.0
    de Does, J, Niestadt, J and Depuydt, K. 2017. Creating Research Environments with BlackLab. In: Odijk, J and van Hessen, A. (eds.) CLARIN in the Low Countries, Pp. 245–257. London: Ubiquity Press. DOI: https://doi.org/10.5334/bbi.20. License: CC-BY 4.0
    Oostdijk, N., Reynaert, M., Hoste, V., Schuurman, I. (2013) The Construction of a 500 Million Word Reference Corpus of Contemporary Written Dutch in: Essential Speech and Language Technology for Dutch: Results by the STEVIN-programme (eds. P. Spyns, J. Odijk), Springer Verlag.

  • CLARIN Concept Registry

    The CCR is a concept registry according to the W3C SKOS recommendation. It was chosen by CLARIN to serve as a semantic registry to overcome semantic interoperability issues with CMDI metadata and different annotation tag sets used for linguistic annotation. The CCR is part of the CMDI metadata infrastructure. The W3C SKOS recommendation, and the OpenSKOS implementation thereof, provides the means for ‘data-sharing, bridging several different fields of knowledge, technology and practice’. According to this model, each concept is assigned a unique administrative identifier, together with information on the status or decision-making process associated with the concept. In addition, concept specifications in the CCR contain linguistic descriptions, such as definitions and examples, and can be associated with a variety of labels. .