| 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. | |
| other,12-1-P82-1035,ak | designed under the assumption that the <term> | input text | </term> will be in reasonably neat form , | #14245 Most large text-understanding systems have been designed under the assumption that theinput text will be in reasonably neat form, e.g., newspaper stories and other edited texts. | |
| other,23-1-P82-1035,ak | be in reasonably neat form , e.g. , <term> | newspaper stories | </term> and other edited texts . However | #14256 Most large text-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. | |
| 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. | |
| other,16-2-P82-1035,ak | </term> e.g. , memos , rough drafts , <term> | conversation transcripts | </term> etc. , have features that differ | #14279 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, poor syntactic construction, missing periods, etc. | |
| other,27-2-P82-1035,ak | that differ significantly from neat <term> | texts | </term> , posing special problems for readers | #14290 However, a great deal of natural language texts e.g., memos, rough drafts, conversation transcripts etc., have features that differ significantly from neattexts, posing special problems for readers, such as misspelled words, missing words, poor syntactic construction, missing periods, etc. | |
| other,38-2-P82-1035,ak | problems for readers , such as misspelled <term> | words | </term> , missing <term> words </term> , poor | #14301 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 misspelledwords, missing words, poor syntactic construction, missing periods, etc. | |
| other,41-2-P82-1035,ak | misspelled <term> words </term> , missing <term> | words | </term> , poor <term> syntactic construction | #14304 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, missingwords, poor syntactic construction, missing periods, etc. | |
| 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,10-3-P82-1035,ak | to these problems is to make use of <term> | expectations | </term> , based both on knowledge of surface | #14325 Our solution to these problems is to make use ofexpectations, based both on knowledge of surface English and on world knowledge of the situation being described. | |
| other,21-3-P82-1035,ak | knowledge of surface English and on <term> | world knowledge | </term> of the situation being described | #14336 Our solution to these problems is to make use of expectations, based both on knowledge of surface English and onworld knowledge of the situation being described. | |
| other,1-4-P82-1035,ak | situation being described . These <term> | syntactic and semantic expectations | </term> can be used to figure out unknown | #14345 Thesesyntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word-senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). | |
| other,14-4-P82-1035,ak | used to figure out unknown words from <term> | context | </term> , constrain the possible <term> word-senses | #14358 These syntactic and semantic expectations can be used to figure out unknown words fromcontext, constrain the possible word-senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). | |
| other,19-4-P82-1035,ak | context </term> , constrain the possible <term> | word-senses | </term> of <term> words </term> with multiple | #14363 These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possibleword-senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). | |
| other,21-4-P82-1035,ak | possible <term> word-senses </term> of <term> | words | </term> with multiple <term> meanings </term> | #14365 These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word-senses ofwords with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). | |
| other,24-4-P82-1035,ak | </term> of <term> words </term> with multiple <term> | meanings | </term> ( <term> ambiguity </term> ) , fill in | #14368 These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word-senses of words with multiplemeanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). | |
| other,26-4-P82-1035,ak | with multiple <term> meanings </term> ( <term> | ambiguity | </term> ) , fill in missing words ( <term> | #14370 These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word-senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). | |
| other,34-4-P82-1035,ak | </term> ) , fill in missing words ( <term> | ellipsis | </term> ) , and resolve <term> referents </term> | #14378 These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word-senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). | |
| other,39-4-P82-1035,ak | <term> ellipsis </term> ) , and resolve <term> | referents | </term> ( <term> anaphora </term> ) . This method | #14383 These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word-senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolvereferents (anaphora). | |
| other,41-4-P82-1035,ak | and resolve <term> referents </term> ( <term> | anaphora | </term> ) . This method of using expectations | #14385 These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word-senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). |
