AIC Seminar Series
Regulatory Conformance Checking Logic and Logical Form
|Nikhil Dinesh||University of Pennsylvania||[Home Page]|
Notice: Hosted by Vinay Chaudhri.
Date: 2010-06-03 at 16:00
Location: EJ228 (SRI E building). slides via WebEx from 3:45pm on, sound at 1-888-355-1249, 749045 (Directions)
We consider the problem of checking whether an organization conforms
to a body of regulation. Conformance is studied in a runtime
verification setting. The regulation is translated to a logic, from
which we synthesize monitors. The monitors are evaluated as the state
of an organization evolves over time, raising an alarm if a violation
is detected. An important challenge to this approach comes from the
fact that regulations are commonly expressed in natural language. The
translation to logic is difficult. Our goal is to assist in this
translation by: (a) the design of logics that let us formalize
regulation one sentence at a time, and (b) the use of natural language
processing as an aid in the sentential translation.
There are many features that are needed in a logic, to accommodate a
sentential translation of regulation. We study two such features,
motivated by a case study. First, statements in regulation refer to
others for conditions or exceptions. Second, sentences in regulation
convey legal concepts, e.g., obligation and permission. Obligations
and permissions can be nested to convey concepts, such as, rights. We
motivate and design a logic to accomodate these two features of
regulatory texts. An underlying theme is the importance of the notion
of ``saying in such constructs.
We then turn to the use of natural language processing to translate a
sentence to logic. We study one component of the translation in a
supervised learning setting. Linguistic theories have argued for a
level of logical form as a prelude to translating a sentence into
logic. Logical form encodes a resolution of both predicate-argument
structure, and scope ambiguities. We define a restricted kind of
logical form, called ``abstract syntax trees (ASTs), based on the
logic developed. We describe a modest sized corpus of
ASTs annotated on the Food and Drug Administrations Code
of Federal Regulations (FDA CFR), and ongoing experiments on
learning to compute ASTs.
Nikhil Dinesh received the B.E. degree in Computer Science from the Regional Engineering College, Trichy, India. He is currently a Ph. D. candidate in Computer Science at the University of Pennsylvania, expecting to graduate in July 2010. His research interests include formal verification, logic, and natural language processing. For his PhD thesis, he focused on the problem of translating regulatory documents to logic, for the applications of conformance checking and access control. He has also been involved in developing the Penn Discourse Treebank, which provides a level of discourse structure and semantics on the Wall Street Journal corpus.
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