A text corpus of one hundred and one Marian Miracle stories in Old Swedish written between c. 1272 and 1430 has been digitally compiled from three transcribed sources from the 19th Century. Highly specialized knowledge is needed to interpret these texts, since the medieval variant of Swedish differs significantly from the modern form of the language. Both the vocabulary and spelling as well as the grammar show substantial variances compared to modern Swedish. To advance the understanding of these texts, automated tools for textual processing are needed. This paper preliminary investigates a number of strategies, such as frequency list analysis and methods for identifying spelling variations for producing stop word lists and exposing the key words of the texts. This can be a help to understand the texts, identifying different word forms of the same word, to ease a lexicon lookup and be a starting point for lemmatisation.
The purpose with this article is to first make a brief presentation of the functions in the web based text processing tool Textin 1.2, and then to illuminate these functions by putting the program to use within a research project in progress that concerns developmental aspects on texts written by Swedish pupils during school years 5 to 9. The text will begin with a brief description of Textins’ main functions, and then move on to previous research on school texts where computer linguistic methods either were used or could have been used if the technology had been accessible at the time being. The article then continues with a presentation of the results that Textin delivers, and ends with a discussion on these findings.
In this paper, we describe our work on building a parallel treebank for a less studied and typologically dissimilar language pair, namely Swedish and Turkish. The treebank is a balanced syntactically annotated corpus containing both fiction and technical documents. In total, it consists of approximately 160,000 tokens in Swedish and 145,000 in Turkish. The texts are linguistically annotated using different layers from part of speech tags and morphological features to dependency annotation. Each layer is automatically processed by using basic language resources for the involved languages. The sentences and words are aligned, and partly manually corrected. We create the treebank by reusing and adjusting existing tools for the automatic annotation, alignment, and their correction and visualization. The treebank was developed within the project Supporting research environment for minor languages aiming at to create representative language resources for language pairs dissimilar in language structure. Therefore, efforts are put on developing a general method for formatting and annotation procedure, as well as using tools that can be applied to other language pairs easily.
We describe a syntactically annotated parallel corpus containing typologically partly different languages, namely English, Swedish and Turkish. The corpus consists of approximately 300 000 tokens in Swedish, 160 000 in Turkish and 150 000 in English, containing both fiction and technical documents. We build the corpus by using the Uplug toolkit for automatic structural markup, such as tokenization and sentence segmentation, as well as sentence and word alignment. In addition, we use basic language resource kits for the linguistic analysis of the languages involved. The annotation is carried on various layers from morphological and part of speech analysis to dependency structures. The tools used for linguistic annotation, e.g. HunPos tagger and MaltParser, are freely available data-driven resources, trained on existing corpora and treebanks for each language. The parallel treebank is used in teaching and linguistic research to study the relationship between the structurally different languages. In order to study the treebank, several tools have been developed for the visualization of the annotation and alignment, allowing search for linguistic patterns.