Papers by Katrin Ortmann

    2 papers
    Automatic Orality Identification in Historical Texts (2020.lrec-1)

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    Challenge: a set of general linguistic features are used to identify conceptually-oral historical texts . linguists recognize that there is also a lot of variation within discourse modes .
    Approach: They propose to use general linguistic features to identify conceptually-oral historical texts . they find they are useful for determining conceptuality of historical data as for modern data .
    Outcome: The proposed features are used to identify conceptually-oral historical German texts . the features are useful in determining conceptuality of historical data as they are for modern data .
    Fine-Grained Error Analysis and Fair Evaluation of Labeled Spans (2022.lrec-1)

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    Challenge: Annotations with incorrect label or boundaries count as two errors instead of one, despite being closer to the target annotation than false positives or false negatives.
    Approach: They propose an algorithm for error identification in flat and multi-level annotations and propose a procedure for calculating meaningful precision, recall, and F1-scores based on the more fine-grained error types.
    Outcome: The proposed procedure prevents double penalties and allows for a more detailed error analysis, providing more insight into the actual weaknesses of a system.

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