Word sense alignment and disambiguation for historical encyclopedias
This paper will address the challenge of creating a knowledge graph from a corpus of historical encyclopedias with a special focus on word sense alignment (WSA) and disambiguation (WSD). More precisely, we examine WSA and WSD approaches based on...
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This paper will address the challenge of creating a knowledge graph from a corpus of historical encyclopedias with a special focus on word sense alignment (WSA) and disambiguation (WSD). More precisely, we examine WSA and WSD approaches based on article similarity to link messy historical data, utilizing Wikipedia as aground-truth component – as the lack of a critical overlap in content paired with the amount of variation between and within the encyclopedias does not allow for choosing a ”baseline” encyclopedia to align the others to. Additionally, we are comparing the disambiguation performance of conservative methods like the Lesk algorithm to more recent approaches, i.e. using language models to disambiguate senses.
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LRTwiki: enriching the likelihood ratio test with encyclopedic information for the extraction of relevant terms
This paper introduces LRTwiki, an improved variant of the Likelihood Ratio Test (LRT). The central idea of LRTwiki is to employ a comprehensive domain specific knowledge source as additional “on-topic” data sets, and to modify the calculation of the...
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This paper introduces LRTwiki, an improved variant of the Likelihood Ratio Test (LRT). The central idea of LRTwiki is to employ a comprehensive domain specific knowledge source as additional “on-topic” data sets, and to modify the calculation of the LRT algorithm to take advantage of this new information. The knowledge source is created on the basis of Wikipedia articles. We evaluate on the two related tasks product feature extraction and keyphrase extraction, and find LRTwiki to yield a significant improvement over the original LRT in both tasks.
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Knowledge sources for bridging resolution in multi-party dialog
In this paper we investigate the coverage of the two knowledge sources WordNet and Wikipedia for the task of bridging resolution. We report on an annotation experiment which yielded pairs of bridging anaphors and their antecedents in spoken...
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In this paper we investigate the coverage of the two knowledge sources WordNet and Wikipedia for the task of bridging resolution. We report on an annotation experiment which yielded pairs of bridging anaphors and their antecedents in spoken multi-party dialog. Manual inspection of the two knowledge sources showed that, with some interesting exceptions, Wikipedia is superior to WordNet when it comes to the coverage of information necessary to resolve the bridging anaphors in our data set. We further describe a simple procedure for the automatic extraction of the required knowledge from Wikipedia by means of an API, and discuss some of the implications of the procedure’s performance.
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Learning from students. On the design and usability of an e-dictionary of mathematical graph theory
We created a prototype of an electronic dictionary for the mathematical domain of graph theory. We evaluate our prototype and compare its effectiveness in task-based tests with that of Wikipedia. Our dictionary is based on a corpus; the terms and...
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We created a prototype of an electronic dictionary for the mathematical domain of graph theory. We evaluate our prototype and compare its effectiveness in task-based tests with that of Wikipedia. Our dictionary is based on a corpus; the terms and their definitions were automatically extracted and annotated by experts (cf. Kruse/Heid 2020). The dictionary is bilingual, covering German and English; it gives equivalents, definitions and semantically related terms. For the implementation of the dictionary, we used LexO (Bellandi et al. 2017). The target group of the dictionary are students of mathematics who attend lectures in German and work with English resources. We carried out tests to understand which items the students search for when they work on graph-theoretical tasks. We ran the same test twice, with comparable student groups, either allowing Wikipedia as an information source or our dictionary. The dictionary seems to be especially helpful for students who already have a vague idea of a term because they can use the resource to check if their idea is right.
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Alles okay! Korpusgestützte Untersuchungen zum Internationalismus OKAY
Das Kapitel beschreibt zwei Studien zum Gebrauch des Internationalismus OKAY im Deutschen und Französischen. Die medienvergleichende Studie nutzt Daten aus dem deutschen Gesprächskorpus FOLK (Forschungs- und Lehrkorpus Gesprochenes Deutsch) und aus...
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Das Kapitel beschreibt zwei Studien zum Gebrauch des Internationalismus OKAY im Deutschen und Französischen. Die medienvergleichende Studie nutzt Daten aus dem deutschen Gesprächskorpus FOLK (Forschungs- und Lehrkorpus Gesprochenes Deutsch) und aus einem Korpus mit schriftlichen deutschen Wikipediadiskussionen, um Unterschiede zwischen schriftlicher und mündlicher Verwendung von OKAY zu ermitteln und Hypothesen aus der Fachliteratur zu überprüfen. Die sprachvergleichende Studie vergleicht deutsche und französische Wikipediadiskussionen an Datensets aus der Wikipedia-Korpusfamilie des IDS. Wir beschreiben das Vorgehen bei der Erhebung, Bereinigung und Analyse der Daten, und zeigen, welche Ansatzpunkte für weiterführende Studien sich aus unseren Ergebnissen eröffnen.
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