{'fraction_non_alphanumeric': 0.01583531274742676, 'fraction_numerical': 0.0, 'mean_word_length': 5.448979591836735, '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}}
Diagrams and Text as Computer Input

Diagrams are both natural and economical as a means of describing spatial objects and relationships. The use of relatively free-form diagrams as input to computer programs is potentially very attractive. However, understanding diagrams involves many of the same problems as understanding natural language: ambiguity of diagram elements and relationships, properties that are implicit rather than being explicitly shown, and the need to use context and world knowledge to resolve ambiguities. We describe a program, BEATRIX, that can understand textbook physics problems specified by a combination of English text and a diagram. The result of the understanding process is a unified internal model that represents information derived from both the text and the diagram. The process of interpreting diagram elements and relationships is described; a central problem is establishing coreference, that is, determining when parts of the text and diagram refer to the same object. Constraints supplied by the text, by the diagram, and by world knowledge are sued to reduce ambiguity of diagram elements until unique interpretations are obtained. Generalizations of these techniques to other diagram understanding tasks are discussed.