Web-based Annotation Tool for Inflectional Language Resources

We present Wasim, a web-based tool for semi-automatic morphosyntactic annotation of inflectional languages resources. The tool features high flexibility in segmenting tokens, editing, diacritizing, and labelling tokens and segments. Text annotation of highly inflectional languages (including Arabic) requires key functionality which we could not see in a survey of existing tools. Wasim integrates with morphological analysers to speed up the annotation process by selecting one from their proposed analyses. It integrates as well with external POS taggers for kick-start annotation and adaptive predicting based on annotations made so far. It aims to speed up the annotation by completely relying on a keyboard interface, with no mouse interaction required. Wasim has been tested on four case studies and these features proved to be useful. The source-code is released under the MIT license

An automatic part-of-speech tagger for Middle Low German

Syntactically annotated corpora are highly important for enabling large-scale diachronic and diatopic language research. Such corpora have recently been developed for a variety of historical languages, or are still under development. One of those under development is the fully tagged and parsed Corpus of Historical Low German (CHLG), which is aimed at facilitating research into the highly under-researched diachronic syntax of Low German. The present paper reports on a crucial step in creating the corpus, viz. the creation of a part-of-speech tagger for Middle Low German (MLG). Having been transmitted in several non-standardised written varieties, MLG poses a challenge to standard POS taggers, which usually rely on normalized spelling. We outline the major issues faced in the creation of the tagger and present our solutions to them

CLASSLA-Stanza: The Next Step for Linguistic Processing of South Slavic Languages

We present CLASSLA-Stanza, a pipeline for automatic linguistic annotation of the South Slavic languages, which is based on the Stanza natural language processing pipeline. We describe the main improvements in CLASSLA-Stanza with respect to Stanza, and give a detailed description of the model training process for the latest 2.1 release of the pipeline. We also report performance scores produced by the pipeline for different languages and varieties. CLASSLA-Stanza exhibits consistently high performance across all the supported languages and outperforms or expands its parent pipeline Stanza at all the supported tasks. We also present the pipeline's new functionality enabling efficient processing of web data and the reasons that led to its implementation.Comment: 17 pages, 14 tables, 1 figur

A Task-based Evaluation of French Morphological Resources and Tools

Morphology is a key component for many Language Technology applications. However, morphological relations, especially those relying on the derivation and compounding processes, are often addressed in a superficial manner. In this article, we focus on assessing the relevance of deep and motivated morphological knowledge in Natural Language Processing applications. We first describe an annotation experiment whose goal is to evaluate the role of morphology for one task, namely Question Answering (QA). We then highlight the kind of linguistic knowledge that is necessary for this particular task and propose a qualitative analysis of morphological phenomena in order to identify the morphological processes that are most relevant. Based on this study, we perform an intrinsic evaluation of existing tools and resources for French morphology, in order to quantify their coverage. Our conclusions provide helpful insights for using and building appropriate morphological resources and tools that could have a significant impact on the application performance