ds-to-ps conversion fei xia university of washington july 29, 2011 1
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DS-to-PS conversion
Fei XiaUniversity 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 guidelines4
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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)25
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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)27
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Can DS and PS be inconsistent?• DS and PS can represent different aspects of the same
overall 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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