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ORGANIZER;CN=Robin Gandhi;SENT-BY="MAILTO:[email protected]":MAIL
 TO:[email protected]
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=spdx@lists
 .spdx.org:MAILTO:[email protected]
DESCRIPTION;LANGUAGE=en-US:All\,\nI’m forwarding this on behalf of Robin 
 from UNO. As you know\, UNO has been highly supportive of SPDX. The resear
 ch Robin is discussing is outside of the scope of SPDX\, but may be of int
 erest to some.\nPhil\n\n\n\nOn 7/6/17\, 4:15 PM\, "Robin Gandhi" <rgandhi@
 unomaha.edu> wrote:\n\n    Webinar:\n    Join the call: https://www.uberco
 nference.com/robinagandhi\n    Optional dial in number: 585-632-5623  PIN:
  86451\n    **Best to join using a computer as I will using screen share f
 or the demonstration.**\n    \n    When:\n    Meeting Time: Thurs\, July 1
 3\, 8am PDT / 10 am CDT / 11am EDT / 15:00 UTC. http://www.timeanddate.com
 /worldclock/converter.html\n    \n    Note:\n    Hello all\,\n    Please c
 onsider attending this conference call to provide feedback on a method to 
 model legal text and its use for compliance analysis. The discussion will 
 demonstrate associated tool support and discuss related model semantics.\n
     \n    Here is an abstract from a recent paper that our team authored:\
 n    \n    Modular Norm Models: A Frame-Semantic Approach\n    Abstract—
  Norms in contractual agreements include claim-rights and corresponding du
 ties. Analysis of norms expressed in voluminous legal text can benefit fro
 m the automation and traceability of logic-based models. Such norm models 
 help reason about available rights and required duties based on the satisf
 iability of situations\, a state-of-affair\, in a given scenario. But mode
 l extraction from natural language needs subject matter expertise. Complia
 nce reasoning in complex scenarios using large norm model networks is also
  difficult. We outline a novel method for modular norm model extraction an
 d reasoning. For extraction\, using the theory of frame-semantics we const
 ruct two foundational norm templates that cover Hohfeld’s concepts of cl
 aim-right and its jural correlative\, duty. Template instantiations from l
 egal text result in a re- peatable method for extraction of modular norm m
 odels. For reasoning\, we introduce the notion of a super-situation. Super
 - situations contain other norm models. Compliance results from a modular 
 norm are propagated to its containing super-situation\, which in turn part
 icipates in other modular norms. This modularity allows on-demand incremen
 tal modeling and reasoning using simpler model primitives than previous ap
 proaches. We show our method on a variety of contractual statements in pri
 vacy and open source software domains.\n    \n    Here is the Github repos
 itory with some demonstration links:  https://github.com/robinagandhi/modu
 larnorms\n    \n
UID:E23AA5A7-2427-42D7-999B-E110D4BA515A
SUMMARY;LANGUAGE=en-US:FW: Modeling Legal Text: A Tool Demonstration
DTSTART;TZID=Central Standard Time:20170713T100000
DTEND;TZID=Central Standard Time:20170713T110000
CLASS:PUBLIC
PRIORITY:5
DTSTAMP:20170706T201526Z
TRANSP:OPAQUE
STATUS:CONFIRMED
SEQUENCE:1
LOCATION;LANGUAGE=en-US:Join the call: https://www.uberconference.com/robin
 agandhi\nOptional dial in number: 585-632-5623\nPIN: 86451
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