Controlled Natural Language Generation from a Multilingual FrameNet-based Grammar
Graph Methods for Multilingual FrameNets...The FrameNet lexical database as a set of graphsFN...
Transcript of Graph Methods for Multilingual FrameNets...The FrameNet lexical database as a set of graphsFN...
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Graph Methods for Multilingual FrameNets
Collin F. Baker Michael J. Ellsworth
International Computer Science InstituteBerkeley, California
TextGraphsACL 2017
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Overview
The FrameNet lexical database as a set of graphs
FrameNet annotation as graphs
Syntactico-semantic annotation graphs of parallel sentences
Graph methods and Conclusions
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
The Multilingual FrameNet Project
• Goals:• Organize and align existing FrameNet-like projects in 8-10
languages• Provide a multilingual language resource to NLP research,
language teachers, etc.• Improve access to and understanding of FrameNet data
from all languages (both lexicon and annotated texts)• Research questions:
• What data structures are appropriate for the new resource?• How “universal” are semantic frames? What are
implications for MT, cross-linguistic IE & IR, etc.?• How can graph methods help us achieve these goals? We
hope to receive suggestions from the TextGraph community
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Frames, Frame elements, Lemmas and Lexical units• Frames and Frame Elements (FEs)
Judgement: Cognizer , Evaluee , Reason , etc.Placing: Agent , Theme , Goal , etc.Take place of: New , Old , Role , Time , etc.Everyone ADMIRES her for working so hard .I HANG my clothes in the wardrobeBy 1803 cotton REPLACED wool as Britain’s leading export
• Frames and Lexical Units (LUs)Judgement: admire.v, contempt.n, stigmatize.v, reverence.nPlacing: place.v., drape.v, cram.v, file.vTake place of: replace.v, replacement.n, take place of.v
• 1,223 frames, 10,542 FEs (9.7/frame), 13,634 LUs(12.5/frame), 202,229 annotation sets
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Frames, Frame elements, Lemmas and Lexical unitsas a graph
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Frames, Frame elements, Lemmas and Lexical unitsas a graph
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Frames, Frame elements, Lemmas and Lexical unitsas a graph
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Frame relations
• Inheritance• Perspective on (full example)• Subframe and Precedes• Others
• Using• Causative of, Inchoative of• Metaphor• "See also"
All frame relations are accompanied by relations betweencorresponding frame element across the frames.
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“Perspective on” frame relations
Note that reality is more complex; Quitting and Firing are notthe same kind of event, there are many ways employment canend: resigning under pressure, retirement, etc.
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Frame Grapher
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Graph of FrameNet semantic types (partial)
Animate_being
Sentient
Human
Artifact
Structure
Body_of_water
Running_water
Living_thing Location
Region Point Line
Landform
Physical_entity
[...] Physical_object
Body_part Container
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
FN Annotation (Annotator’s view)
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
FN Annotation (XML view)
<sentence sentNo="0" aPos="102894573" ID="695812"><text>Dr Farmery blames the Department of Health for causing undue alarm, but thatclaim’s rejected by the Helpline set up to address public concern. </text>
<annotationSet cDate="01/07/2003 11:09:51 PST Tue" status="MANUAL"ID="867585">
<layer rank="1" name="FE"><label cBy="BoC" feID="115" end="9" start="0" name="Cognizer"/><label cBy="BoC" feID="116" end="41" start="18" name="Evaluee"/><label cBy="BoC" feID="117" end="65" start="43" name="Reason"/>
</layer>
<layer rank="1" name="GF"><label end="9" start="0" name="Ext"/><label end="41" start="18" name="Obj"/><label end="65" start="43" name="Dep"/>
</layer>
<layer rank="1" name="PT"><label end="9" start="0" name="NP"/><label end="41" start="18" name="NP"/><label end="65" start="43" name="PPing"/>
</layer>
<layer rank="1" name="Target"><label cBy="BoC" end="16" start="11" name="Target"/>
</layer></annotationSet></sentence>
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Annotation of a sentence as a graph (1)
everyone admires her for working so hard
NP
SJudgement
T
ExtCognizer
NP
ObjEvaluee
PPing
DepReason
Marker VPing
Sem Head
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Annotation of a sentence as a graph (2)
everyone admires her for working so hard
NP
SJudgement
T
ExtCognizer
1 NP
ObjEvaluee PPing
DepReason
Marker
VPingWork
Sem Head
T DNI
Goal
1
Agent
AVP
Manner
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Grammatical Function, Phrase Type, and Other layers
• Construction Grammar is presupposed in FN syntacticanalysis, but not fully explicit in the annotation.
• Grammatical functions (GFs)• "External"• "Obj"• "Dep"• Modified head
• Phrase types (PTs)• NP, VPto, AdjP, etc.
• "Other" layer• Relativizer and Antecedent
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An English sentence for analysis
We will be looking at (a clause from) a sentence from a TEDtalk by Ken Robinson: “Do Schools Kill Creativity?”:
The thing they were good at at school was notvalued or was actually stigmatized.
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Syntactic (constituency) tree of sentence
the thing
they were
good
at at
school
was n't valued
or
was actually stigmatized
S
NP
Ext
VP
Head
Rel-clause
NP
Ext
VP
Head
NP
Head
ModHead Conj
VP
Head
VP
Head
Head
AP
PP
Head
Head
PP
Head Mod Head Mod
Head
NP
Head
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Syntactico-semantic graph of English sentence
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Syntactico-semantic graph of parallel Japanesesentence
学校はgakkou wa
school-TOPIC
彼らのkarera no
their
才能をsainou o
talent-ACC
評価しhyoukashi-
value
Positive_judgement
ない-nainot
どころかdokorokainstead
ダメdame
unacceptibleNegative_judgement
だdabe
とto
QUOT
烙印をrakuin o
brand-ACC
押しoshi-press
てしまう-te shimau"end up"
NP: EXPERTISE
Skill T[2] N
Protagonist
VP: JUDGEMENT
T
ObjEvaluee
1
Cognizer
AUX: NEGATION
T
VP: LABELING+Aux
VP: LABELING
Sem Head
AUX
Aux
[1] NPVP: JUDGEMENT
LABELING+Conjunction
Conjunction Head
VP: JUDGEMENT+NEGATION
Head
AdjP: DESIRABILITY
T
2
Entity
Sfin: DESIRABILITY
CopSem Head
と-P: DESIRABILITY
MarkerSem Head
NP
Label
VP
T
1
Speaker
2
Entity
UtteranceS: JUDGEMENT
LABELING+Conjunction
Ext Head
Head Negated_p Aux
Supp
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Semantics-only graph of English sentence
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Frame shifts in translation
We examined frames in two different semantic domains, in twodocuments with different styles of translation:
• Sherlock Holmes, The Hound of the Baskervilles(professional, “literary” translation)– Motion events
• TED, “Do Schools Kill Creativity?” (volunteer, “literal”translation)– Motion and Communication events
Source Langs Domain Same Partial Diff. TotalHound EN–ES Motion 33 3 23 59TED EN–BrPT Motion 38 4 22 64TED EN–BrPT Commun. 47 11 7 65
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Frame Shifts in the Communication Domain
he turned to her mother and said,’Mrs.Lynne,. . .
Statement.say
ele se virou para a mãe e disse:’Sra.Lynne,. . .
Statement.dizer
I said, ’What happened?’ Statement.sayEu perguntei: ’O que aconteceu?’ Questioning.perguntarShe said, “She did.” Statement.sayEla respondeu: Ela levou. Communication_response
responderI mean, he was seven at some point. Linguistic_meaning.meanQuero dizer, ele algum dia teve seteanos.
Statement dizer
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Uses of Graph methods with Frame SemanticAnnotation and Parsing
• Visualize of complex relations, including cross-lingualrelations
• Query with graph expressions (e.g. using Neo4j DB)• Express constraints as graph unification (≈ Construction
grammar)• Summarize valences (Kernel Dependency Graphs, cf.
Fillmore & Sato 2002)
NP
S or VPJudgement
ExtCognizer
NP
ObjEvaluee
PPing
DepReason
admire
T
for
Marker
VPing
Sem Head
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Conclusions
• The current XML format is too close to the DB structure,less than optimal for both humans and machines
• A more perspicuous representation would helpcollaboration in Multilingual FrameNet and NLP researchmore generally
• Graphs can serve this purpose• We welcome your suggestions about how we can make
better use of graph representations!
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Acknowledgements
This material is based in part upon work supported by theNational Science Foundation under grant No. 1629989”Multilingual FrameNet: A Resource Enabling Cross-LingualResearch for the Natural Language Processing Community”.
• Thank you!• Questions?• http://framenet.icsi.berkeley.edu
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The FrameNet lexical database as a set of graphs FN annotation Sentences Conclusions References
Semantics-only graph of parallel Japanese sentence
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FILLMORE, CHARLES J., & HIROAKI SATO.2002.Transparency and building lexical dependency graphs.In Proceedings of the 28th Annual Meeting of the BerkeleyLinguistics Society , ed. by J. Larson & M. Paster, 87–99.