Controlled Languages for Knowledge Representation in FOL

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Controlled Languages for Knowledge Representation
in FOL
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• Motivation
• Translate (contrived) English into FOL without
  solving NLU.

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Natural English
Controlled English
MOCL English
T-Complete Formalisms
Spec. Lang.
FOL
L-CL
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• Commonly Referenced L-CLs
• Controlled Language for Inference Purposes (CLIP)
  Sukkarieh2003
• Controlled English to Logic Translation (CELT)
  PeaseMurray2003
• Attempto Controlled English (ACE)
  FuchsSchwertelSchwitter1999
• Processable English (PENG) Schwitter2002
• Common Logic Controlled English (CLCE)Sowa2004
• Several Others (not considered here)

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(No Transcript)
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CLIP

• Attributes
• McLogic McAllesterGivan1992
• Montagovian syntax (Richard Montague 1930-71)
• Syllogistic Reasoning
• Criticisms
• Lots of inference rules (34) including both
  forward and backwards chaining
• Each new language construct can introduce new
  inference rules

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Schuberts Steamroller in McLogic
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CELT

• Ostensibly KIF plus ACE (minus a few features)
  coupled with WordNet and SUMO
• WordNet provides a very large initial vocabulary
  and CELT automates the process of mapping
  sentences with terms from WordNet to their more
  formal representations in KIF formulas and the
  Standard Upper Merged Ontology.
  PeaseMurray2003
• Also mapped to PhaseBank PeaseFellbaum2004

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CELT KIF Example
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PENG

• Also ostensibly ACE (minus a few features)
• Has a nice editor ECOLE (unification-based
  grammar formalism)
• Schwitter was a major contributor to ACE
• Schwitter also investigates techniques to convert
  English into Controlled English

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ACE

• Predefined Function words
• determiners,
• Prepositions,
• Conjunctions,
• User-defined content words
• nouns,
• verbs,
• adjectives,
• Construction Rules
• Interpretation Rules
• Unification-based Phase Structure Grammar
• Single unambiguous semantic interpretation (even
  if the English seems ambiguous)

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Simple ACE Sentences

• subject verb complements adjuncts
• A new customer inserts 2 valid cards.
• Johns customer inserts a card of Mary.
• The customer Mr Miller inserts a card A.
• A customer who is new inserts a card that he
  owns.
• A customer inserts some cards manually.
• A customer manually inserts not more than 2
  cards.
• A customer inserts a card into a slot.
• Johns customer who is new inserts a valid card
  of Mary manually into a slot A.
• ???

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Composite ACE Sentences

• Recursively built from simple sentences using
  Coordination (and, or)
• A customer inserts 2 cards and the machine checks
  their codes.
• Subordination (who, which, that)
• A customer who is new inserts a card that he
  owns.
• Quantification
• Every customer inserts a card.
• Negation
• No customer inserts more than 2 cards.
  ???

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ACE Interpretation Rules

• The customer inserts a card with a code.
• Rule
• A prepositional phrase always modifies the verb.
• Interpretation
• The customer inserts a card with a code.
• The customer inserts a card that carries a code.
• Rule
• A relative sentence always modifies the
  immediately preceding noun phrase.
• Interpretation
• The customer inserts a card that carries a
  code.

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ACE and DRS

• Every company that buys a standard machine gets a
  discount. A British company buys a standard
  machine.
• paragraph(
• drs(A,B,C,drs(D,E,F,object(D,company)-1,str
  ucture(D,atomic)-1,
• object(E,machine)-1, structure(E,atomic)-1,
  property(E,standard)-1,
• predicate(F,event,buy,D,E)-1) gt
  drs(G,H,object(G,discount)-1,
• structure(G,atomic)-1, predicate(H,event,get,D,G)
  -1),
• object(A,company)-2, structure(A,atomic)-2,
  property(A,'British')-2,
• object(B,machine)-2, structure(B,atomic)-2,
  property(B,standard)-2,
• predicate(C,event,buy,A,B)-2),
• text('Every company that buys a standard
  machine gets a discount.', 'A British company
  buys a standard machine.'))
• FuchsSchwertel2003

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ACE Future Work

• Fixed Modal Phrases
• can, cannot, must, must not, is/does always,
  is/does never

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CLCE

• Strong ties to CL, KIF and CGIF
• Little information available (not a single
  published work on CLCE)
• Grammar Specification is incomplete
• No Parser publicly available but the claim is
• Under the assumption that all words, names, and
  variables are declared explicitly or implicitly
  before their first use, the translation of any
  CLCE text to FOL can be performed in a single
  pass by a context-free parser augmented with two
  symbol tables Sowa2004

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CLCE Grammar

• Sentences
• Simple, Complex, Compound
• Declarative, Interrogative, Imperative
• Extended Sentences (ie. Paragraphs)

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CLCE Grammar

• Reserved Words
• Boolean operators
• not, and, either, or, neither, nor, if, then.
• Quantifiers
• a, an, some, something, someone, every,
  everything, everyone, no, nothing, no one.
• Special verbs is, has, have, does.
• Interrogatives who, what, when, where, which.
• Relative pronoun that.
• Definite article the.
• List connector and.
• Special lists none, others, nothing else, no one
  else.
• Argument markers of, than, as.
• Special phrases
• there is, such that, only if, if and only if, it
  is false that, is it true that.

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CLCE Example

• CLCE
• Every ancestor of a person x is either a parent
  of x or a parent of an ancestor of x.
• FOL
• (?y)(?xPerson)(Ancestor(y,x) ? (Parent(y,x) ?
  (?z)(Parent(y,z) ? Ancestor(z,x))))
• CGIF
• (Ancestor _at_lambda Personx) _at_everyy
  Either Or (Parent ?y ?x) Or (Parent ?y
  z) (Ancestor ?z ?x)

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• Commonly Cited Books
• L. M. Iwanska and S. C. Schapiro (eds). Natural
  Language Processing and Knowledge Representation.
  AAAI Press. 2000.
• H. Kamp and U. Reyle. From Discourse to Logic,
  Introduction to Modeltheoretic Semantics of
  Natural Language, Formal Logic and Discourse
  Representation Theory. 1993.
• P. Blackburn and J. Bos. Representation and
  Inference for Natural Language A First Course in
  Computational Semantics. 2005.
• P. Blackburn and J. Bos. Working with Discourse
  Representation Theory An Advanced Course in
  Computational Semantics. Forthcoming.

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References

• Sukkarieh. Mind your Language! Controlled
  Language for Inference Purposes. Controlled
  Language Application Workshop (CLAW2003). Dublin,
  Ireland. 2003.
• J. Sukkarieh and S. G. Pulman. Computer
  Processable English and McLogic. In Proceedings
  of the Third International Workshop on
  Computational Semantics, Tilburg, The
  Netherlands. 1999.
• D. McAllester, R. Givan, and S. Shalaby. Natural
  Language Syntax and First Order Inference.
  Artificial Intelligence. 561-20. 1992.
• A. Pease and W. Murray. An English to Logic
  Translator for Ontology-based Knowledge
  Representation Languages. In IEEE International
  Conference on Natural Language Processing and
  Knowledge Engineering. Beijing, China. 2003.
• A. Pease and C. Fellbaum. Language to Logic
  Translation with PhraseBank. Second International
  WordNet Conference (GWC2004). 2004.
• N. E. Fuchs, U. Schwertel, R. Schwitter. Attempto
  Controlled English (ACE) Language Manual, Version
  3.0, Technical Report  99.03. Department of
  Computer Science, University of Zurich, August
  1999.
• R. Schwitter. English as a Formal Specification
  Language. Proceedings of the Thirteenth
  International Workshop on Database and Expert
  Systems Applications (DEXA 2002), W04 Third
  International Workshop on Natural Language and
  Information Systems - NLIS, 2-6 September 2002,
  Aix-en-Provence, France, pp. 228-232, 2002.
• N. E. Fuchs, U. Schwertel. Reasoning in Attempto
  Controlled English. In Principles and Practice of
  Semantic Web Reasoning, International Workshop
  PPSWR 2003 Lecture Notes in Computer Science
  2901. Springer Verlag. 2003.
• J. F. Sowa. Common Logic Controlled English
  (CLCE). http//www.jfsowa.com/clce/specs.htm. 2004

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Backup Material
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History of Controlled Languages
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Birth of CL 1920s 30s

• Motivation
• The search for a common scientific language
  when Latin stopped serving that purpose.
  Sukkarieh2003
• Notable CLs
• Esperanto
• British American Scientific International
  Commercial (BASIC) English

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Growth of CL 1970s 80s

• Motivation
• Improve readability of technical writing
  (manuals) especially for those knowing little
  English.
• Notable CLs
• Caterpillar Fundamental English (CFE)
• Douglas Aircraft Simplified English
• AECMA Simplified Technical English (SE)

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Present Day CL 1990s present

• Motivation
• Simplify written communication
• Decrease ambiguity
• Enable translation

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Present Day CL 1990s present

• Notable CLs
• International Language of Service and Maintenance
  (ILSAM)
• Bull Global English
• Perkins/Univ. Edinburgh PACE
• GIFAS Rationalized French
• General Motors Global English
• Securities and Exchange Commission (SEC) Plain
  English
• Controlled Spanish
• Caterpillar Technical English (CTE)
• Attempto Controlled English (ACE)
• Alcatel COGRAM
• Xerox Multilingual Customized English
• Kodak International Service Language
• IBM Easy English
• General Motors Controlled Automotive Service
  Language (CASL)
• ProLingua LinguaNet
• Diebold Controlled English
• Scania Swedish
• Nortel Standard English (NSE)

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2 Axis Continuum for CLs

• Axis 1
• HOCL
• Human-Oriented Controlled Language Huijsen1998
• improves readability and comprehensibility
• CPCL (MOCL)
• Computer Processable Controlled Language
  Pulman1996
• Machine-Oriented Controlled Language
• Improves translatability
• Axis 2
• Monolingual
• Single CL (or several related by core rules)
• Multilingual
• Multi CLs via machine-oriented translation
  processing techniques

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References

• Sukkarieh. Mind your Language! Controlled
  Language for Inference Purposes. Controlled
  Language Application Workshop (CLAW2003). Dublin,
  Ireland. 2003.
• Jeffrey Allen and Kathleen Barthe. Introductory
  overview of Controlled Languages. Invited talk
  presented at the Society for Technical
  Communication meeting of the Paris, France
  chapter. Paris, France. 2004.
• Willem-Olaf Huijsen. Controlled Language An
  Introduction. Controlled Language Application
  Workshop (CLAW1998). Pittsburgh, PA. 1998.
• Pulman. Controlled Language for Knowledge
  Representation. Controlled Language Application
  Workshop (CLAW1996). Leuven, Belgium. 1996.