BY PHILIPP CIMIANO PRESENTED BY JOSEPH PARK CONCEPT HIERARCHY INDUCTION.
NLDB 2004 ORAKEL: A Natural Language Interface to an F-Logic Knowledge Base Philipp Cimiano...
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Transcript of NLDB 2004 ORAKEL: A Natural Language Interface to an F-Logic Knowledge Base Philipp Cimiano...
NLDB 2004
ORAKEL: A Natural Language Interface to an F-Logic Knowledge
Base
Philipp Cimiano
Institute AIFB
University of Karlsruhe
NLDB 2004
NLDB 2004
Outline Aim & Scope System Architecture F-Logic in a Nutshell Semantic Construction Component Lexicon Generation Component Conclusion & Further Work
NLDB 2004
Aims & Scope Aim: accessing a KB via natural
language translating language into logical queries
Who owns a company? Who owns every company? Who does not own a company?
Scope: consider only factoid questions simple syntactic structure: SVO +PP?
NLDB 2004
System Architecture
General Lexicon
Domain Lexicon
Lexicon Generation
Parsing + Sem.Construction
NL query
answer
F-Logic KBOntobroker
logicalquery
NLDB 2004
F-Logic in A Nutshell frames/methods:
microsoft[name ->„Microsoft“;
boss -> bill_gates; revenue(2002) -> 28.370.000.000]
subclasses: company::organization class-membership: microsoft:company queries: ][:? microsoftownXbossX
NLDB 2004
Semantic Construction compositional semantics approach to
map NL questions to F-Logic queries relies on LTAG-style parsing
formalism developed in [Muskens 01] extension to accommodate
ontological concepts [Cimiano & Reyle 03]
NLDB 2004
Who owns Microsoft?
)(:.
:
1
1
XQpersonXQ
personwh
wh
Who
)(21
1
swhs i
s
12
2
vps
s
},{ bossbosswh CCi
1dp1vp
))((.12
2
ZZ
vp
vdpvp
][.. YownXYX
v
v companydp 1
ie
owns
NLDB 2004
Who owns Microsoft?)(
21
1
swhs i
s
12
2
vps
s
},{ bossbosswh CCi
1dp1vp
))((.12
2
ZZ
vp
vdpvp
][.. YownXYX
v
v companydp 1
ie
owns
)(:.
:
1
1
XQpersonXQ
personwh
wh
Who
)(.
:
2
2
microsoftPP
companydp
dp
Microsoft
NLDB 2004
Who owns Microsoft?
)(:.
:
1
1
XQpersonXQ
personwh
wh
Who
)(21
1
swhs i
s
12
2
vps
s
},{ bossbosswh CCi
1dp1vp
))((.12
2
ZZ
vp
vdpvp
][.. YownXYX
v
v companydp 1
ie
owns )(.
:
2
2
microsoftPP
companydp
dp
Microsoft
43?3
ss
s
4s ?
NLDB 2004
Who owns Microsoft?)(
21
1
swhs i
s
12
2
vps
s
},{ bossbosswh CCi
1dp1vp
))((.12
2
ZZ
vp
vdpvp
][.. YownXYX
v
v companydp 1
ie
owns
)(:.
:
1
1
XQpersonXQ
personwh
wh
Who
)(.
:
2
2
microsoftPP
companydp
dp
Microsoft
43?3
ss
s
4s ?
NLDB 2004
Who owns Microsoft?
)(:.
:
1
1
XQpersonXQ
personwh
wh
Whov
43?3
ss
s
4s ?
)(21
1
swhs i
s
12
2
vps
s
},{ bossbosswh CCi
1dp1vp
][.2
2
microsoftownZZ
vp
vp
ie
owns
companydp :2
Microsoft
NLDB 2004
Who owns Microsoft?
43?3
ss
s
4s ?
][:1
microsoftownXpersonX
s
2s
1dp 1vp
companydp :2
personwh :1
v
Who
owns Microsoft
ei
NLDB 2004
Who owns Microsoft?
1s
2s
1dp 1vp
companydp :2
personwh :1
v
Who
owns Microsoft
ei
][:?3
microsoftownXpersonX
s
?
NLDB 2004
Lexicon Generation (part I) person[own->company]
use corpus (BNC) parse it (LoPar) extract with tgrep
S V O (transitive) S V PP (intransitive + PP) S V O PP (transitive + PP) N PP N PP PP
find most appropriate synset for each argument w.r.t WordNet [Resnik 97]
NLDB 2004
Lexicon Generation (part II)
person[own -> company]
own:transitive: (45.90%)
subj: 100001740obj: 100001740
instransitive + PP: (4.10%)subj: 100001740PP(by): 100017954
take the one maximizing:
repeat the whole process with synonyms of most frequent synset, i.e. have and possess
)|())(),((
1
),(
vsPjcic v
ji WN
NLDB 2004
Lexicon Generation (part III)
person[own->company] own(subj: person, obj: company)
Generate elementary trees: Who owns Microsoft? Which company does Bill Gates own? Which company is owned by Bill
Gates?
NLDB 2004
Lexicon Generation (part IV)
)(.
:
2
2
microsoftPP
companydp
dp
Microsoft
Microsoft:company
)(.
:
2
2
xcompanyx
companynp
dp
company
NLDB 2004
Evaluation 5 ontologies from the DAML library:
beer wine personal information general information about organizations university activities
acquire an appropriate subcategorization frame for the binary relations
NLDB 2004
Results
Ontology
#Props
Dom.+Range
Non-Composite
Correct
%
Beer 9 4 3 2 66.67
Wine 10 10 9 6 44.44
Personal 25 10 8 6 75
General 28 17 6 6 100
University
27 11 2 1 50
Total 99 42 28 21 75
NLDB 2004
ConclusionORAKEL: translating NL questions into logical form theoretical (parsing) framework lexicon generation
differs from: AQUALOG (map triples to an ontology) FrameNet (mapping lexical/semantic
representations) AID (use TFIDF-based similarity) Schema-based (map words to database columns)
NLDB 2004
Further WorkFurther applications:
NL generation from an ontology Mapping from syntax to ontological
structures (MOSES)
Further Work: user feedback answer formulation real life evaluation application to construct the KB
NLDB 2004
EKAW 2004 Workshop on the Application of Language and Semantic
Technologies to support Knowledge Management
Submission deadline: 4. July!!!
Topics:
Multi-lingual systems, Information Extraction, Ontology Learning, Document Indexing, Retrieval and Browsing, Approaches to Semantic Annotation, Smart Browsing, Semantic Search, Question Answering, Enterprise Content Management
Organizing Committee:
Philipp Cimiano, AIFB, University of Karlsruhe, Germany. Fabio Ciravegna, Natural Language Processing Group, University of Sheffield, UK Enrico Motta, Knowledge Media Institute, The Open University, UK. Victoria Uren, Knowledge Media Institute, The Open University, UK.