| other,44-2-P82-1035,ak | </term> , missing <term> words </term> , poor <term> | syntactic construction | </term> , missing periods , etc . Our solution | #14307 However, a great deal of natural language texts e.g., memos, rough drafts, conversation transcripts etc., have features that differ significantly from neat texts, posing special problems for readers, such as misspelled words, missing words, poorsyntactic construction, missing periods, etc. | |
| other,6-2-P82-1035,ak | texts . However , a great deal of <term> | natural language texts | </term> e.g. , memos , rough drafts , <term> | #14269 However, a great deal ofnatural language texts e.g., memos, rough drafts, conversation transcripts etc., have features that differ significantly from neat texts, posing special problems for readers, such as misspelled words, missing words, poor syntactic construction, missing periods, etc. | |
| tech,2-1-P82-1035,ak | executed to yield the answer . Most large <term> | text-understanding systems | </term> have been designed under the assumption | #14235 Most largetext-understanding systems have been designed under the assumption that the input text will be in reasonably neat form, e.g., newspaper stories and other edited texts. | |
| tool,21-5-P82-1035,ak | a working computer program called <term> | NOMAD | </term> , which understands scruffy <term> | #14409 This method of using expectations to aid the understanding of scruffy texts has been incorporated into a working computer program calledNOMAD, which understands scruffy texts in the domain of Navy messages. |
