Difference between revisions of "Vulcan/TextualMatching"

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== Overview ==
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Rules should be human readable and based on textual tuples.  They should be in a format that is easy for  manual creation and editing.  The human-readable rules can be automatically transformed into TUFFY format.
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The set of facts used by the system are stored as textual tuples with a link to the sentence and the genre (e.g. definition, study guide, ClueWeb).  These tuples may be nested or n-ary, and may have null arg2 for intransitive relations.  These tuples can be automatically transformed into TUFFY format.
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Rule: <id> (Arg|Rel) : (<var>|<string>) => (Arg|Rel) : (<var>|<string>) <comment>
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Notes: Rule looks for exact string match in either an Arg or Rel phrase
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<var> can be X, Y, Z, R,… and must match any other instances of same variable.
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<comment> may be displayed in derivation
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Example 1
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Question to demonstrate: “Growth causes leaves of a plant to become large”.
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(growth, cause,  (leaves of a plant, become large)) [nested, with intransitive arg2]
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(growth, cause,  (leaves of a plant, become, large)) [nested, with binary rel for arg2]
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Evidence from definition: “The noun growth is the process of something becoming bigger”
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(growth, is process of, (something, become bigger)
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(growth, is process of, (something, become, bigger))
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Rules needed:
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1. Rel: X  =>  Rel: is process of [generalize any action to “is process of”]
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1a. Rel: cause  =>  Rel: is process of [more particular version of rule 2]
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2. Rel: is process of  =>  Rel: X [abductive rule, inverse of rule 1]
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2a. Rel: is process of  =>  Rel: cause [abductive rule, inverse of rule 1a]
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3. Arg: X  => Arg: something [generalize any arg value to “something”]
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4. Arg: something  =>  Arg: X [abductive rule, inverse of rule 3]
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5. Rel: become bigger  =>  Rel: become big [lexical substitution from verb stemmer]
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6. Rel: become big  =>  Rel: become large [lexical substitution from WN synonym]
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Notes on rules:
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We can derive abductive inverses automatically with a meta-rule.
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Lexical substitution rules are generated on the fly as needed.
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Derivation:
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Evidence:
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(growth, is process of, (something, become bigger))
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Rel: become bigger  =>  Rel: become big
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(growth, is process of, (something, become big))
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Rel: become big  =>  Rel: become large
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(growth, is process of, (something, become large))
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Arg: something  =>  Arg: X
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(growth, is process of, (leaves of a plant, become large))
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Rel: is process of  =>  Rel: X
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(growth, cause,  (leaves of a plant, become large))  QED
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Example 2
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Question to demonstrate: “A sense of smell helps a fox find food”
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(sense of smell, helps,  (fox, find, food))
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Evidence from Study Guide: “A good sense of smell is necessary for many animals to find food.”
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(good sense of smell, is necessary for, (animal, find, food))
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Rules needed:
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7. Rel: is necessary for  =>  Rel: helps [a textual entailment]
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8. Arg: fox  =>  Arg: animal [lexical substitution from WN hypernym]
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9. Arg: animal  => Arg: fox [lexical specialization from WN hypernym]
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10.  Arg: X Y  => Arg: Y [generalize by dropping modifier]
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10a.  Arg: good Y  => Arg: Y [more particular version of rule 10]
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10b.  Arg: good sense of smell  => Arg: sense of smell [more particular version of rule 10a]
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11.  Arg: Y  => Arg: X Y [abductive inverse of rule 10]
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11a.  Arg: Y  => Arg: good Y [more particular version of rule 11]
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11b.  Arg: sense of smell => Arg: good sense of smell [more particular version of rule 11a]
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Note on rules:
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10 and 10a are in the nature of meta-rules – TUFFY gets the particular rule 10b.  Same with 11, 11a, 11b.
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Derivation:
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Evidence:
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(good sense of smell, is necessary for, (animal, find, food))
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Arg: good Y  => Arg: Y
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(sense of smell, is necessary for, (animal, find, food))
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Arg: animal  => Arg: fox
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(sense of smell, is necessary for, (fox, find, food))
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Rel: is necessary for  =>  Rel: helps
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(sense of smell, helps, (fox, find, food))
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<!--
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Logic style matching can limit recall during inference. Here we discuss some examples of the types of fuzzy textual matching that we need to support.
 
Logic style matching can limit recall during inference. Here we discuss some examples of the types of fuzzy textual matching that we need to support.
  
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100 users(uid, name, hashedPswd), easyPasswords(p), [md5(hashedPswd) = p] => cracked(name, p).
 
100 users(uid, name, hashedPswd), easyPasswords(p), [md5(hashedPswd) = p] => cracked(name, p).
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-->

Revision as of 22:43, 19 August 2013

Overview

Rules should be human readable and based on textual tuples. They should be in a format that is easy for manual creation and editing. The human-readable rules can be automatically transformed into TUFFY format.

The set of facts used by the system are stored as textual tuples with a link to the sentence and the genre (e.g. definition, study guide, ClueWeb). These tuples may be nested or n-ary, and may have null arg2 for intransitive relations. These tuples can be automatically transformed into TUFFY format.

Rule: <id> (Arg|Rel) : (|<string>) => (Arg|Rel) : (|<string>) <comment> Notes: Rule looks for exact string match in either an Arg or Rel phrase can be X, Y, Z, R,… and must match any other instances of same variable. <comment> may be displayed in derivation Example 1 Question to demonstrate: “Growth causes leaves of a plant to become large”. (growth, cause, (leaves of a plant, become large)) [nested, with intransitive arg2] (growth, cause, (leaves of a plant, become, large)) [nested, with binary rel for arg2]

Evidence from definition: “The noun growth is the process of something becoming bigger” (growth, is process of, (something, become bigger) (growth, is process of, (something, become, bigger)) Rules needed: 1. Rel: X => Rel: is process of [generalize any action to “is process of”] 1a. Rel: cause => Rel: is process of [more particular version of rule 2] 2. Rel: is process of => Rel: X [abductive rule, inverse of rule 1] 2a. Rel: is process of => Rel: cause [abductive rule, inverse of rule 1a] 3. Arg: X => Arg: something [generalize any arg value to “something”] 4. Arg: something => Arg: X [abductive rule, inverse of rule 3] 5. Rel: become bigger => Rel: become big [lexical substitution from verb stemmer] 6. Rel: become big => Rel: become large [lexical substitution from WN synonym] Notes on rules: We can derive abductive inverses automatically with a meta-rule. Lexical substitution rules are generated on the fly as needed. Derivation: Evidence: (growth, is process of, (something, become bigger)) Rel: become bigger => Rel: become big (growth, is process of, (something, become big)) Rel: become big => Rel: become large (growth, is process of, (something, become large)) Arg: something => Arg: X (growth, is process of, (leaves of a plant, become large)) Rel: is process of => Rel: X (growth, cause, (leaves of a plant, become large)) QED

  Example 2 Question to demonstrate: “A sense of smell helps a fox find food” (sense of smell, helps, (fox, find, food)) Evidence from Study Guide: “A good sense of smell is necessary for many animals to find food.” (good sense of smell, is necessary for, (animal, find, food)) Rules needed: 7. Rel: is necessary for => Rel: helps [a textual entailment] 8. Arg: fox => Arg: animal [lexical substitution from WN hypernym] 9. Arg: animal => Arg: fox [lexical specialization from WN hypernym] 10. Arg: X Y => Arg: Y [generalize by dropping modifier] 10a. Arg: good Y => Arg: Y [more particular version of rule 10] 10b. Arg: good sense of smell => Arg: sense of smell [more particular version of rule 10a] 11. Arg: Y => Arg: X Y [abductive inverse of rule 10] 11a. Arg: Y => Arg: good Y [more particular version of rule 11] 11b. Arg: sense of smell => Arg: good sense of smell [more particular version of rule 11a] Note on rules: 10 and 10a are in the nature of meta-rules – TUFFY gets the particular rule 10b. Same with 11, 11a, 11b. Derivation: Evidence: (good sense of smell, is necessary for, (animal, find, food)) Arg: good Y => Arg: Y (sense of smell, is necessary for, (animal, find, food)) Arg: animal => Arg: fox (sense of smell, is necessary for, (fox, find, food)) Rel: is necessary for => Rel: helps (sense of smell, helps, (fox, find, food))