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This general strategy will be illustrated by a practical application , namely the << highlighting of relevant information >> in a patient discharge summary -LRB- PDS -RRB- by means of modern [[ HyperText Mark-Up Language -LRB- HTML -RRB- technology ]] . | USED-FOR | [
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Such an [[ application ]] can be of use for << medical administrative purposes >> in a hospital environment . | USED-FOR | [
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<< CriterionSM Online Essay Evaluation Service >> includes a capability that labels sentences in student writing with [[ essay-based discourse elements ]] -LRB- e.g. , thesis statements -RRB- . | PART-OF | [
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CriterionSM Online Essay Evaluation Service includes a capability that labels sentences in student writing with << essay-based discourse elements >> -LRB- e.g. , [[ thesis statements ]] -RRB- . | HYPONYM-OF | [
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We describe a new [[ system ]] that enhances << Criterion 's capability >> , by evaluating multiple aspects of coherence in essays . | USED-FOR | [
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We describe a new << system >> that enhances Criterion 's capability , by evaluating multiple aspects of [[ coherence in essays ]] . | EVALUATE-FOR | [
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This [[ system ]] identifies << features >> of sentences based on semantic similarity measures and discourse structure . | USED-FOR | [
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This system identifies << features >> of sentences based on [[ semantic similarity measures ]] and discourse structure . | USED-FOR | [
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This system identifies << features >> of sentences based on semantic similarity measures and [[ discourse structure ]] . | USED-FOR | [
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This system identifies features of sentences based on << semantic similarity measures >> and [[ discourse structure ]] . | CONJUNCTION | [
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A << support vector machine >> uses these [[ features ]] to capture breakdowns in coherence due to relatedness to the essay question and relatedness between discourse elements . | USED-FOR | [
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A support vector machine uses these [[ features ]] to capture << breakdowns in coherence >> due to relatedness to the essay question and relatedness between discourse elements . | USED-FOR | [
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<< Intra-sentential quality >> is evaluated with [[ rule-based heuristics ]] . | EVALUATE-FOR | [
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Results indicate that the [[ system ]] yields higher performance than a << baseline >> on all three aspects . | COMPARE | [
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This paper presents an [[ algorithm ]] for << labeling curvilinear structure >> at multiple scales in line drawings and edge images Symbolic CURVE-ELEMENT tokens residing in a spatially-indexed and scale-indexed data structure denote circular arcs fit to image data . | USED-FOR | [
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This paper presents an algorithm for << labeling curvilinear structure >> at multiple scales in [[ line drawings ]] and edge images Symbolic CURVE-ELEMENT tokens residing in a spatially-indexed and scale-indexed data structure denote circular arcs fit to image data . | FEATURE-OF | [
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This paper presents an algorithm for labeling curvilinear structure at multiple scales in [[ line drawings ]] and << edge images >> Symbolic CURVE-ELEMENT tokens residing in a spatially-indexed and scale-indexed data structure denote circular arcs fit to image data . | CONJUNCTION | [
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This paper presents an algorithm for << labeling curvilinear structure >> at multiple scales in line drawings and [[ edge images ]] Symbolic CURVE-ELEMENT tokens residing in a spatially-indexed and scale-indexed data structure denote circular arcs fit to image data . | FEATURE-OF | [
16,
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This paper presents an algorithm for labeling curvilinear structure at multiple scales in line drawings and edge images Symbolic [[ CURVE-ELEMENT tokens ]] residing in a << spatially-indexed and scale-indexed data structure >> denote circular arcs fit to image data . | PART-OF | [
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