To maintain the de facto standard to NLPre evaluation, we apply the evaluation measures defined for the CoNLL 2018 shared task and implemented in the official evaluation script. Our focus is on F1 and AlignedAccuracy, which is similar to F1 but does not consider possible misalignments in tokens, words, or sentences. This ensures consistency in how we assess various natural language processing tools and their effectiveness.
In our evaluation process, we follow default training procedures suggested by the authors of the evaluated systems. We deliberately choose not to conduct any optimal hyperparameter search, favoring the recommended model configuration as-is. This decision is crucial as it allows us to assess the tools based on their intended operational settings and offers a clearer understanding of their performance in real-world applications.
#natural-language-processing #evaluation-methodology #conll-2018 #model-configuration #benchmarking-tools
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