Challenges in the Alignment, Management and Exploitation of Large and Richly Annotated Multi-Parallel Corpora

The availability of large multi-parallel corpora offers an enormous wealth of material to contrastive corpus linguists, translators and language learners, if we can exploit the data properly. Necessary preparation steps include sentence and word alignment across multiple languages. Additionally, linguistic annotation such as part-of-speech tagging, lemmatisation, chunking, and dependency parsing facilitate precise querying of linguistic properties and can be used to extend word alignment to sub-sentential groups. Such highly inter-connected data is stored in a relational database to allow for efficient retrieval and linguistic data mining, which may include the statistics-based selection of good example sentences. The varying information needs of contrastive linguists require a flexible linguistic query language for ad hoc searches. Such queries in the format of generalised treebank query languages will be automatically translated into SQL queries. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-111877 Veröffentlichte Version Originally published at: Graën, Johannes; Clematide, Simon (2015). Challenges in the alignment, management and exploitation of large and richly annotated multi-parallel corpora. In: 3rd Workshop on the Challenges in the Management of Large Corpora, Lancaster, 20 Juli 2015 20 Juli 2015, 15-20. Challenges in the Alignment, Management and Exploitation of Large and Richly Annotated Multi-Parallel Corpora Johannes Graën Institute of Computational Linguistics University of Zurich Zurich, Switzerland [email protected] Simon Clematide Institute of Computational Linguistics University of Zurich Zurich, Switzerland [email protected]