AceRules: Executing Rules in Controlled Natural Language

Tobias Kuhn(University of Zurich)

RR2007Innsbruck

8 June 2007

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Introduction

Domain specialists that are supposed to create and/or validate rules are often not familiar with formal languages

Verbalization of the rules in natural language becomes necessary

Translation of rules into NL (and backwards) is complicated and a potential source of errors

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The AceRules Approach

Expressing rules in controlled natural language

Attempto Controlled English (ACE)

http://attempto.ifi.uzh.ch formal and human readable

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Attempto Controlled English (ACE)

Developed at the University of Zurich

Formal language with a restricted English grammar

ACE supports: quantification, negation, conditional sentences, modality, active & passive voice, singular & plural, relative clauses, conjunction & disjunction, anaphoric references, pronouns, variables, commands, queries, macros

ACE texts can be translated automatically and unambiguously into first-order logic

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ACE as a Rule Language:

Some Examples

John is an important customer.customer('John') <-important('John') <-

No clerk is a customer.-customer(A) <- clerk(A)

Everyone who is not provably a criminal is trustworthy.trustworthy(A) <- ~criminal(A)

If a resource is public then every user can download the resource.can(download(A,B)) <- user(A), resource(B), public(B)

If a user is authenticated and has a subscription and there is a resource that is available for the subscription then the user can download the resource.can(download(A,B)) <- be_available_for(B,C), have(A,C), resource(B), subscription(C), user(A), authenticated(A)

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AceRules

Input and output in controlled natural language (ACE)

Forward chaining interpreters

John is a man.Every man is a human.Mary is a woman.Every woman is a human.No man is a woman and no woman is a man.Everyone who is not provably a criminal is trustworthy.John is a criminal.No criminal is trustworthy.Every human who is trustworthy gets a credit-card from BankX.

Mary is trustworthy.BankX is trustworthy.Mary is a woman.Mary is a human.John is a man.John is a human.John is a criminal.Mary gets a credit-card from BankX.It is false that John is trustworthy.It is false that John is a woman.It is false that Mary is a man.

Program: Answer:

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Semantics

Semantics are exchangeable

Currently supported semantics:

Courteous logic programs

Stable models

Stable models with strong negation

Other semantics (i.e. interpreters) could be incorporated with little integration effort.

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Web Interface

http://attempto.ifi.uzh.ch/acerules

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The Missing Link:Authoring Tool

Problem: How to learn writing in ACE?

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Thank you for your attention!

Questions?

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Architecture

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Comparison of the Semantics