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<\/figure>\n\n\n\nAs can be seen, 13 out of 15 non-English words are annotated and analysed as a proper noun – which obviously does not make sense, as a sentence just cannot only be made up of proper nouns. Hence, this already confirms the prediction of a tendency to categorise non-English words as proper nouns.<\/p>\n\n\n\n
However, there are also two exceptions: siempre and la. Siempre is categorised as a verb, la as a determiner. Which is however, also not completely correct. ‚La‘ is a determiner as it is an article, however, ’siempre‘ is – if my broken Spanish is anything to be sure of – an adverb, as it means always.\u00a0I do not really have an answer as to why these two words are exceptions, and especially not why one is still falsely while the other is correctly analysed.<\/p>\n\n\n\n
Hence, most of our initial predictions did come true while working with ANNIS. This is obviously not a great result in terms of correctly annotating and tokenising sentences, however, in terms of emphasising the problem of an anglocentric view and an Anglocentrism in software developing, it is a very telling result.<\/p>\n","protected":false},"excerpt":{"rendered":"
Working with the software ANNIS and the corpus consisting of our novels\u2019 example sentences, one of the predictions we had at the beginning of term came true: Machine annotation is indeed faulty and there is a tendency to classify non-English … Weiterlesen