{'fraction_non_alphanumeric': 0.015105740181268883, 'fraction_numerical': 0.0, 'mean_word_length': 6.366666666666666, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Explanations in the Information Extraction System iDocument

The information extraction system iDocument interactively extracts information from texts such as instances and relations with respect to existing background knowledge. An extraction process creates weighted hypotheses describing indications of relevant information. During execution, each process step records its output into an instantiated process model. We reused these bits of information for generating conceptual, functional as well as causal explanations. In order to visualise explanations, our component utilises different mechanisms for textual, explorative, and pictorial rendering styles.