DS-to-PS conversion Fei Xia University of Washington July 29, 2011 - - PowerPoint PPT Presentation

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DS-to-PS conversion Fei Xia University of Washington July 29, 2011 - - PowerPoint PPT Presentation

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DS-to-PS conversion Fei Xia University of Washington July 29, 2011 1 Main steps in building the treebank DS treebank: Tokenization Morphological analysis, voice, etc. POS tagging DS Propbank: adding Predicate-argument

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DS-to-PS conversion

Fei Xia University of Washington July 29, 2011

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Main steps in building the treebank

  • DS treebank:

– Tokenization – Morphological analysis, voice, etc. – POS tagging – DS

  • Propbank: adding Predicate-argument info
  • Automatic DS-to-PS conversion
  • Some manual check to ensure the conversion works well

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Outline

  • Important concepts
  • Compatibility and consistency
  • Handling inconsistency

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Important concepts

  • Linguistic phenomena
  • Representation type
  • Linguistic theory

– Theoretical framework – Linguistic analyses

  • Annotation guidelines

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Linguistic phenomena

  • They are what we want to present, including

– General concepts: e.g., which words form a phrase? What types of phrases does a language have? – Types of relations between words or phrases (e.g., subjecthood, temporal modification) – Specific constructions (e.g., small clause) – Finer-grained distinctions (e.g., unergative vs. unaccusative)

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Representation type

  • It is the type of mathematical object that is used to

represent syntactic facts

  • Examples: DS, PS
  • Each representation type can decide what more

specific representation devices to employ – Labels on the arcs of a tree – Use of empty nodes or coindexation between nodes

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Linguistic theory

  • It explains how linguistic phenomena are

represented in the chose representation type

  • It has two components:

– Theoretical framework: it provides vocabulary and constraints in which linguistic theories can be formulated: e.g., GB, LFG, LTAG, HPSG – Linguistic analyses

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Small clause

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“Exceptional case-marking” analysis

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“Raising-to-object” analysis

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Annotation guidelines

  • Guideline designers need to choose the following

– Linguistic phenomena to represent – Representation type – Theoretical framework – Linguistic analyses – Descriptions – Examples: sentences with DS or PS trees

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Outline

  • Important concepts
  • Compatibility and consistency
  • Handling inconsistency

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“Exceptional case-marking” analysis

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“Raising-to-object” analysis

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Implicit vs. explicit information

  • Certain aspects of information has to be

expressed explicitly in DS, but not PS, or vice versa

– Head in DS – Syntactic categories of phrases in PS

  • Not explicitly providing info does not mean

that corresponding concepts does not exist in DS/PS

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Syntactic consistency

  • We assume each phrase in a PS has a special

word, head word, which represents the property of the phrase.

  • A (DS, PS) pair is called consistent if there is a

way to assign a head word to each internal node in the PS so that the resulting DS is identical to the given DS.

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Consistent pairs

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Inconsistent pairs

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A real example

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Consistency assumption

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Definition of consistency

  • A DS and a PS are consistent iff there exists a

flattened version of the PS that is identical to the DS.

  • If the input DS and the desired PS are

consistent, the PS can be created by stretching the DS and adding syntactic labels.

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Checking consistency

  • For each (dep, head) pair in the DS

– find their location in the PS and their closest antecedent – add heads to the nodes on the path between the leaf nodes and the antecedent

  • The DS and the PS are consistent iff each node

in the PS has exactly one head.

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(Vinken, join)

(Vinken) (join) (join) (join)

(board, join)

(board)

(will, join) (29, join)

(29)

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Outline

  • Important concepts
  • Compatibility and consistency
  • Handling inconsistency

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wh-movement

(who, come)

come come come come come come come

(come, think)

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wh-movement

(who, come) (come, think)

come come come come come | think come | think come

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wh-movement

(who, come) (come, think)

come come come ?? think think ??

(you, think)

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Can DS and PS be inconsistent?

  • DS and PS can represent different aspects of the same
  • verall pictures, and still be consistent.

– Info provided in PropBank: e.g., empty subject, unaccusative – Info that is in PS only: e.g., traces

  • DS and PS should not choose “conflicting” analyses.

– DS and PS are two images of the same underlying treebank, not two separate treebanks. – Ex: ba-construction in Chinese: verb, prep, or something else? – Ex: free relatives: empty nominal head

  • The inconsistency cases should be rare and well-motivated.

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How to handle inconsistency?

  • Detect inconsistency in (DS, PS) pairs in the

guidelines

  • Consult guideline designers to determine

whether the inconsistency can be resolved by changing analyses

  • If not, introduce DScons and ensure sufficient info

is in DS for automatic conversion.

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Two-stage conversion

  • DS to DScons: by removing “inconsistency”

between DS and PS.

  • DScons to PS: by applying conversion rules

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Case #1: long-distance movement

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DSconst:

DSprop:

  • Other examples: extraposition
  • Easily detectable due to non-projectivity
  • Create DSconst by moving up the “moved element” and leaving a trace
  • which node is the “moved element”?

The one that is apart from other nodes in the subtree.

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Case #2: local scrambling

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Detectable by assuming canonical word order: k1 > k2 Need from PS/DS teams the canonical word order and what word order triggers movement

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Case #3: small clause rule

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Detectable by dependency type k2s Need confirmation from IIIT that k2s is used only for small clause

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Case 4: support verb

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Detectable by dependency type “pof” Need confirmation from IIIT that “pof” is used only for support verb

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Conclusion

  • We define consistency between DS and PS
  • DS and PS can be inconsistent but such cases

should be rare and well-motivated.

  • We will handle inconsistency with the two-

stage approach

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Conversion algorithm

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Definition of conversion rule

  • A conversion rule is a (DS_pattern, PS_pattern) pair.
  • Ex:
  • Simplest case:

– DS_pattern corresponds to only one dependency link – Decomposing DS becomes trivial – PS_pattern is a tree fragment (e.g., wh-movement) – Learning rules from (PS, DS) pairs is easy

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Extracting rules

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Rules extracted from the example

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Input DS

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Gluing PS segments together

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c c c

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