Concordance

Query N01-1003 23 >
Shuffle 23 (1,072.3 per million)

other,40-1-N01-1003,bq	<term> Sentence planning </term> is a set of inter-related but distinct tasks , one of which is <term> sentence scoping </term> , i.e. the choice of <term> syntactic structure </term> for elementary <term> speech acts </term> and the decision of how to combine them into one or more <term> sentences </term> .	#1333 Sentence planning is a set of inter-related but distinct tasks, one of which is sentence scoping, i.e. the choice of syntactic structure for elementary speech acts and the decision of how to combine them into one or moresentences.
tech,6-4-N01-1003,bq	First , a very simple , <term> randomized sentence-plan-generator ( SPG ) </term> generates a potentially large list of possible <term> sentence plans </term> for a given <term> text-plan input </term> .	#1380 First, a very simple,randomized sentence-plan-generator ( SPG ) generates a potentially large list of possible sentence plans for a given text-plan input.
other,18-4-N01-1003,bq	First , a very simple , <term> randomized sentence-plan-generator ( SPG ) </term> generates a potentially large list of possible <term> sentence plans </term> for a given <term> text-plan input </term> .	#1392 First, a very simple, randomized sentence-plan-generator (SPG) generates a potentially large list of possiblesentence plans for a given text-plan input.
other,20-5-N01-1003,bq	Second , the <term> sentence-plan-ranker ( SPR ) </term> ranks the list of output <term> sentence plans </term> , and then selects the top-ranked <term> plan </term> .	#1420 Second, the sentence-plan-ranker (SPR) ranks the list of output sentence plans, and then selects the top-rankedplan.
other,12-5-N01-1003,bq	Second , the <term> sentence-plan-ranker ( SPR ) </term> ranks the list of output <term> sentence plans </term> , and then selects the top-ranked <term> plan </term> .	#1412 Second, the sentence-plan-ranker (SPR) ranks the list of outputsentence plans, and then selects the top-ranked plan.
tech,1-6-N01-1003,bq	The <term> SPR </term> uses <term> ranking rules </term> automatically learned from <term> training data </term> .	#1423 TheSPR uses ranking rules automatically learned from training data.
model,3-6-N01-1003,bq	The <term> SPR </term> uses <term> ranking rules </term> automatically learned from <term> training data </term> .	#1425 The SPR usesranking rules automatically learned from training data.
tech,15-1-N01-1003,bq	<term> Sentence planning </term> is a set of inter-related but distinct tasks , one of which is <term> sentence scoping </term> , i.e. the choice of <term> syntactic structure </term> for elementary <term> speech acts </term> and the decision of how to combine them into one or more <term> sentences </term> .	#1308 Sentence planning is a set of inter-related but distinct tasks, one of which issentence scoping, i.e. the choice of syntactic structure for elementary speech acts and the decision of how to combine them into one or more sentences.
tech,9-2-N01-1003,bq	In this paper , we present <term> SPoT </term> , a <term> sentence planner </term> , and a new methodology for automatically training <term> SPoT </term> on the basis of <term> feedback </term> provided by <term> human judges </term> .	#1344 In this paper, we present SPoT, asentence planner, and a new methodology for automatically training SPoT on the basis of feedback provided by human judges.
other,27-2-N01-1003,bq	In this paper , we present <term> SPoT </term> , a <term> sentence planner </term> , and a new methodology for automatically training <term> SPoT </term> on the basis of <term> feedback </term> provided by <term> human judges </term> .	#1362 In this paper, we present SPoT, a sentence planner, and a new methodology for automatically training SPoT on the basis of feedback provided byhuman judges.
other,26-1-N01-1003,bq	<term> Sentence planning </term> is a set of inter-related but distinct tasks , one of which is <term> sentence scoping </term> , i.e. the choice of <term> syntactic structure </term> for elementary <term> speech acts </term> and the decision of how to combine them into one or more <term> sentences </term> .	#1319 Sentence planning is a set of inter-related but distinct tasks, one of which is sentence scoping, i.e. the choice of syntactic structure for elementaryspeech acts and the decision of how to combine them into one or more sentences.
other,23-7-N01-1003,bq	We show that the trained <term> SPR </term> learns to select a <term> sentence plan </term> whose <term> rating </term> on average is only 5 % worse than the <term> top human-ranked sentence plan </term> .	#1456 We show that the trained SPR learns to select a sentence plan whose rating on average is only 5% worse than thetop human-ranked sentence plan.
tech,5-7-N01-1003,bq	We show that the trained <term> SPR </term> learns to select a <term> sentence plan </term> whose <term> rating </term> on average is only 5 % worse than the <term> top human-ranked sentence plan </term> .	#1438 We show that the trainedSPR learns to select a sentence plan whose rating on average is only 5% worse than the top human-ranked sentence plan.
other,22-1-N01-1003,bq	<term> Sentence planning </term> is a set of inter-related but distinct tasks , one of which is <term> sentence scoping </term> , i.e. the choice of <term> syntactic structure </term> for elementary <term> speech acts </term> and the decision of how to combine them into one or more <term> sentences </term> .	#1315 Sentence planning is a set of inter-related but distinct tasks, one of which is sentence scoping, i.e. the choice ofsyntactic structure for elementary speech acts and the decision of how to combine them into one or more sentences.
tech,0-1-N01-1003,bq	Our <term> algorithm </term> reported more than 99 % <term> accuracy </term> in both <term> language identification </term> and <term> key prediction </term> . <term> Sentence planning </term> is a set of inter-related but distinct tasks , one of which is <term> sentence scoping </term> , i.e. the choice of <term> syntactic structure </term> for elementary <term> speech acts </term> and the decision of how to combine them into one or more <term> sentences </term> .	#1293 Our algorithm reported more than 99% accuracy in both language identification and key prediction.Sentence planning is a set of inter-related but distinct tasks, one of which is sentence scoping, i.e. the choice of syntactic structure for elementary speech acts and the decision of how to combine them into one or more sentences.
other,23-4-N01-1003,bq	First , a very simple , <term> randomized sentence-plan-generator ( SPG ) </term> generates a potentially large list of possible <term> sentence plans </term> for a given <term> text-plan input </term> .	#1397 First, a very simple, randomized sentence-plan-generator (SPG) generates a potentially large list of possible sentence plans for a giventext-plan input.
other,10-7-N01-1003,bq	We show that the trained <term> SPR </term> learns to select a <term> sentence plan </term> whose <term> rating </term> on average is only 5 % worse than the <term> top human-ranked sentence plan </term> .	#1443 We show that the trained SPR learns to select asentence plan whose rating on average is only 5% worse than the top human-ranked sentence plan.
lr,8-6-N01-1003,bq	The <term> SPR </term> uses <term> ranking rules </term> automatically learned from <term> training data </term> .	#1430 The SPR uses ranking rules automatically learned fromtraining data.
tech,3-5-N01-1003,bq	Second , the <term> sentence-plan-ranker ( SPR ) </term> ranks the list of output <term> sentence plans </term> , and then selects the top-ranked <term> plan </term> .	#1403 Second, thesentence-plan-ranker ( SPR ) ranks the list of output sentence plans, and then selects the top-ranked plan.
other,24-2-N01-1003,bq	In this paper , we present <term> SPoT </term> , a <term> sentence planner </term> , and a new methodology for automatically training <term> SPoT </term> on the basis of <term> feedback </term> provided by <term> human judges </term> .	#1359 In this paper, we present SPoT, a sentence planner, and a new methodology for automatically training SPoT on the basis offeedback provided by human judges.


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