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This article describes an English Zulu learners’ dictionary that is part of a larger set of information tools, namely an online Zulu course, an e-dictionary of possessives (which was implemented earlier) accompanied by training software offering translation tasks on several levels, and an ontology of morphemic items categorizing and describing all parts of speech of Zulu. The underlying lexicographic database contains the usual type of lexicographic data, such as translation equivalents and their respective morphosyntactic data, but its entries have been extended with data related to the lessons of the online course in order to enable the learner to link both tools autonomously. The ‘outer matter’ is integrated into the website in the form of several texts on additional web pages (how-to-use, typical outputs, grammar tables, information on morphosyntactic rules, etc.). The dictionary comprises a modular system, where each module fulfils one of the necessary functions.
This paper describes general requirements for evaluating and documenting NLP tools with a focus on morphological analysers and the design of a Gold Standard. It is argued that any evaluation must be measurable and documentation thereof must be made accessible for any user of the tool. The documentation must be of a kind that it enables the user to compare different tools offering the same service, hence the descriptions must contain measurable values. A Gold Standard presents a vital part of any measurable evaluation process, therefore, the corpus-based design of a Gold Standard, its creation and problems that occur are reported upon here. Our project concentrates on SMOR, a morphological analyser for German that is to be offered as a web-service. We not only utilize this analyser for designing the Gold Standard, but also evaluate the tool itself at the same time. Note that the project is ongoing, therefore, we cannot present final results.
Corpus-based identification and disambiguation of reading indicators for German nominalizations
(2010)
Corpus data is often structurally and lexically ambiguous; corpus extraction methodologies thus must be made aware of ambiguities. Therefore, given an extraction task, all relevant ambiguities must be identified. To resolve these ambiguities, contextual data responsible for one or another reading is to be considered. In the context of our present work, German -ung-nominalizations and their sortal readings are under examination. A number of these nominalizations may be read as an event or a result, depending on the semantic group they belong to. Here, we concentrate on nominalizations of verbs of saying (henceforth: "verba dicendi"), identify their context partners and their influence on the sortal reading of the nominalizations in question. We present a tool which calculates the sortal reading of such nominalizations and thus may improve not only corpus extraction, but also e.g. machine translation. Lastly, we describe successful attempts to identify the correct sortal reading, conclusions and future work.
In 2010, ISO published a standard for syntactic annotation, ISO 24615:2010 (SynAF). Back then, the document specified a comprehensive reference model for the representation of syntactic annotations, but no accompanying XML serialisation. ISO’s subcommittee on language resource management (ISO TC 37/SC 4) is working on making the SynAF serialisation ISOTiger an additional part of the standard. This contribution addresses the current state of development of ISOTiger, along with a number of open issues on which we are seeking community feedback in order to ensure that ISOTiger becomes a useful extension to the SynAF reference model.
In a previous article (Faaß et al., 2012), a first attempt was made at documenting and encoding morphemic units of two South African Bantu languages, i.e. Northern Sotho and Zulu, with the aim of describing and storing the morphemic units of these two languages in a single relational database, structured as a hierarchical ontology. As a follow-up, the current article describes the implementation of our part-of-speech ontology. We give a detailed description of the morphemes and categories contained in the database, highlighting the need and reasons for a flexible ontology which will provide for both language specific and general linguistic information. By giving a detailed account of the methodology for the population of the database, we provide linguists from other Bantu languages with a road map for extending the database to also include their languages of specialization.
Towards a part-of-speech ontology: encoding morphemic units of two South African Bantu languages
(2012)
This article describes the design of an electronic knowledge base, namely a morpho-syntactic database structured as an ontology of linguistic categories, containing linguistic units of two related languages of the South African Bantu group: Northern Sotho and Zulu. These languages differ significantly in their surface orthographies, but are very similar on the lexical and sub-lexical levels. It is therefore our goal to describe the morphemes of these languages in a single common database in order to outline and interpret commonalities and differences in more detail. Moreover, the relational database which is developed defines the underlying morphemic units (morphs) for both languages. It will be shown that the electronic part-of-speech ontology goes hand in hand with part-of-speech tagsets that label morphemic units. This database is designed as part of a forthcoming system providing lexicographic and linguistic knowledge on the official South African Bantu languages.
Electronic dictionaries should support dictionary users by giving them guidance in text production and text reception, alongside a user-definable offer of lexicographic data for cognitive purposes. In this article, we sketch the principles of an interactive and dynamic electronic dictionary aimed at text production and text reception guiding users in innovative ways, especially with respect to difficult, complicated or confusing issues. The lexicographer has to do a very careful analysis of the nature of the possible problems to suggest an optimal solution for a specific problem. We are of the opinion that there are numerous complex situations where users need more detailed support than currently available in e-dictionaries, enabling them to make valid and correct choices. For highly complex situations, we suggest guidance through a decision tree-like device. We assume that the solutions proposed here are not specific to one language only but can, after careful analysis, be applied to e-dictionaries in different languages across the world.
So far, comprehensive grammar descriptions of Northern Sotho have only been available in the form of prescriptive books aiming at teaching the language. This paper describes parts of the first morpho-syntactic description of Northern Sotho from a computational perspective (Faaß, 2010a). Such a description is necessary for implementing rule based, operational grammars. It is also essential for the annotation of training data to be utilised by statistical parsers. The work that we partially present here may hence provide a resource for computational processing of the language in order to proceed with producing linguistic representations beyond tagging, may it be chunking or parsing. The paper begins with describing significant Northern Sotho verbal morpho-syntactics (section 2). It is shown that the topology of the verb can be depicted as a slot system which may form the basis for computational processing (section 3). Note that the implementation of the described rules (section 4) and also coverage tests are ongoing processes upon that we will report in more detail at a later stage.
In der Computerlinguistik ist eine kaskadische Prozessierung von Texten üblich. Dabei werden diese zuerst segmentiert (tokenisiert), d.h. Tokens und ggf. Satzgrenzen werden erkannt. Dabei entsteht meist eine Liste bzw. eine einspaltige Tabelle, die sukzessive durch weitere Prozessierungschritte um zusätzliche Spalten – also positionale Annotationen wie z.B. Wortarten und Lemmata für die Tokens in der ersten Spalte – ergänzt wird. Bei der Tokenisierung werden alle Spatien (Leerzeichen) gelöscht. Schon immer problematisch waren dabei Interpunktionszeichen, da diese äußerst ambig sein können, aber auch mehrteilige Namen, die Leerzeichen enthalten und eigentlich zusammengehören. Dieser Beitrag fokussiert auf den Apostroph, der in vielfältiger Weise in den Texten Udo Lindenbergs eingesetzt wird sowie auf mehrteilige Namen, die wir als Tokens erhalten möchten. Wir nutzen dafür das komplette Lindenberg-Archiv des song-korpus.de-Repositoriums, kategorisieren die auftretenden Phänomene, erstellen einen Goldstandard und entwickeln ein teils regel-, teils auf maschinellem Lernen basierendes Segmentierungswerkzeug, das insbesondere die auftretenden Apostrophe, aber auch -lexikonbasiert - mehrteilige Namen nach unseren Vorstellungen erkennt und tokenisiert. Im Anschluss trainieren wir den RNN-Tagger (Schmid, 2019) und zeigen auf, dass ein spezifisch für diese Texte angepasstes Training zu Genauigkeiten ≥ 96% führt. Dabei entsteht nicht nur ein Goldstandard des annotierten Korpus, das dem Songkorpus-Repositorium zur Verfügung gestellt wird, sondern auch eine angepasste Version des RNN-Taggers (verfügbar auf github), die für ähnliche Texte verwendet werden kann.