Concordance

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other,37-2-P82-1035,bq	special problems for readers , such as <term>	misspelled words	</term> , <term> missing words </term> , <term>	#13011 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 asmisspelled words, missing words, poor syntactic construction, missing periods, etc.
other,6-2-P82-1035,bq	</term> . However , a great deal of <term>	natural language texts	</term> e.g. , <term> memos </term> , rough <term>	#12980 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,26-2-P82-1035,bq	features that differ significantly from <term>	neat texts	</term> , posing special problems for readers	#13000 However, a great deal of natural language texts e.g., memos, rough drafts, conversation transcripts etc., have features that differ significantly fromneat texts, posing special problems for readers, such as misspelled words, missing words, poor syntactic construction, missing periods, etc.
other,39-4-P82-1035,bq	<term> elllpsis </term> ) , and resolve <term>	referents	</term> ( <term> anaphora </term> ) . This method	#13094 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 (elllpsis), and resolvereferents (anaphora).
other,34-4-P82-1035,bq	fill in <term> missing words </term> ( <term>	elllpsis	</term> ) , and resolve <term> referents </term>	#13089 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 (elllpsis), and resolve referents (anaphora).
other,1-4-P82-1035,bq	situation being described . These <term>	syntactic and semantic expectations	</term> can be used to figure out <term> unknown	#13056 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 (elllpsis), and resolve referents (anaphora).
other,21-3-P82-1035,bq	<term> surface English </term> and on <term>	world knowledge	</term> of the situation being described	#13047 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,40-2-P82-1035,bq	such as <term> misspelled words </term> , <term>	missing words	</term> , <term> poor syntactic construction	#13014 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,27-1-P82-1035,bq	<term> newspaper stories </term> and other <term>	edited texts	</term> . However , a great deal of <term>	#12971 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 otheredited texts.
other,14-4-P82-1035,bq	out <term> unknown words </term> from <term>	context	</term> , constrain the possible <term> word-senses	#13069 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 (elllpsis), and resolve referents (anaphora).
other,13-1-P82-1035,bq	under the assumption that the input <term>	text	</term> will be in reasonably neat form ,	#12957 Most large text-understanding systems have been designed under the assumption that the inputtext will be in reasonably neat form, e.g., newspaper stories and other edited texts.


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