knowledge network based on legal issues - network analysis in law, icail 2013 - paul zhang - harry...

Knowledge Network Based on Legal Issues

- Network Analysis in Law, ICAIL 2013

- Paul Zhang- Harry Silver- Mark D. Wasson- David Steiner- Sanjay Sharma

June, 2013

Research and work has been going on to build networks based on Semantics of text corpora (for both general sources and Legal Documents)

Typically, the basic linguistic units used to represent semantics of texts include: Words and Phrases, Concepts, Topics, Paragraphs, or various types of Entities

Here, we describe a new type of semantic units for Legal Data - units of . . .

Legal Issues

These Legal Issues can be mined from a case law corpus, and be networked to represent knowledge of the legal domain

In this presentation, we focus more on the How-to part of the work. Those interested are invited to read the paper version, where you will find more analysis and examples

We will talk about the following points . . . . . .

Legal Issue Library

Network of Legal Issues

WHY Legal Issues

Representing Cases with Legal Issues

Semantics of Citations

HOW todoit

Why Legal Issues . . .

A Legal Issue (in our context) is a statement of belief, opinion, a legal principle, etc. It usually contains one or more “Concepts” to be meaningful. For example, here is a Statement:

“Thirteen-year-olds should not own a vehicle.”

It has at least three Concepts in it: “13-year-old”, “vehicle”, and “to own”; and the author or speaker states clearly an opinion, a belief, or a rule

Here are examples of Legal Issues:

“An inference is not reasonable if it is based only on speculation.”

“To constitute the crime of robbery, however, the use of force must be motivated by an intent to steal.”

“a statute will not be given an interpretation in conflict with its clear purpose, and that general words used therein will be given a restricted meaning when reason and justice require it, rather than a literal meaning which would lead to an unjust and absurd consequence.”

“… the initial question to be decided in all cases in which a defendant complains of prosecutorial misconduct for the first time on appeal is whether a timely objection and admonition would have cured the harm.”

. . . . . . ,

which can be seen as small pieces of Law in the United Sates

Why Legal Issues . . .

Concepts, on the other hand, are building-blocks of discussion or Issues

The Concept “vehicle”, for example, is used in all these Legal Issues:

“A police officer may approach a stopped vehicle and inquire about an occupant's well-being without intruding on the Fourth Amendment.”

“In Nebraska, a vehicle can be a tool of the debtor's trade if the debtor uses it in connection with or to commute to work.”

“State law governs the issue of security interests in motor vehicles.”

“In Idaho, it is a felony to purport to sell or transfer a vehicle without delivering to the purchaser or transferee a certificate of title duly assigned to the purchaser.”

They are, obviously, on different Issues

▪ Legal Issues are more specific and stand-alone statements relevant to the legal expert’s discussion and argument

▪ While Concepts, Topics and other types of linguistic Units tell us what a legal discussion is generally ABOUT . . . , Legal Issues tell us what the legal discussion is specifically SAYING

As a result, we are able to distinguish between

Case-based Citations vs. Issue-based Citations,

and make citation links more specific:

Case_X:CiteArea_a Case_Y

to

Case_X:CiteArea_a Case_Y:CiteArea_b

The following is an example of such a new Citation Link:


A72D7FE70BE40038 is the ID for the Citing Case : “ROLLEY, INC. v. MERLE NORMAN COSMETICS, INC.” , 129 Cal. App. 2d 844

R_1 represents the Citing RFC in the case : “Appellate courts cannot submit to piecemeal argument and will not consider on petition for rehearing

questions not previously raised.”

A26169830BE40246 is the ID for the Cited Case : “Bradley v. Bradley” , 94 Cal. App. 2d 310

R_5 represents the Cited Text Area in the Case “The case having been tried on the theory that condonation was not an issue appellant under settled principles cannot

now change his theory on [***3] appeal to the disadvantage of respondent.”

( 0.832590108 : the similarity measure )

What this line says : “ROLLEY, INC. v. MERLE NORMAN COSMETICS, INC.” cited “Bradley v. Bradley” for the listed Legal Issue ( with a similarity measure of 0.8 )


A72D7FE70BE40038:R_1::A26169830BE40246:R_5::0.832590108

The Citation corpus is now “Issue-Based”( Colors represent different ISSUEs )

Legal Issue Library

During the process, individual Legal Issues are “chained” together by traversing the Issue-pairs data, and placed in a repository to form the Issue Library

Cases and text areas in them where an Issue was discussed are linked to the Issue in the Library

This corpus is the main source for building the Legal Issue Library

Legal Issue Library

Legal Issue Library

An example Record in LIL with minimum elements:

Legal Issue Library

Most cases have multiple Legal Issues in the text. To some extent, these Legal Issues form a skeleton of the case

With the Issue Library in the background, each case can be converted into a Vector of Legal Issues, which is a new Case Representation that is computable

This new type of metadata looks like this:

( Each LLI has a direct link to a Record in the Issue Library )

Since Issues are uniquely identified and normalized, the new Case Representation can be indexed to support different Applications, such as searching, clustering, content-linking, etc.

As discussed above, Issues are more specific semantically than other Linguistic Units, this new data will provide deeper semantic analytic power for Legal Research

Case ID : Legal Issues found in Case

CASE_00000001: LLI_000055; LLI_000195; LLI_000220; LLI_112160; . . . CASE_00000002: LLI_000089; LLI_000220; LLI_112160; LLI_115095; LLI_200344; . . CASE_00000003: LLI_000455; LLI_001178; LLI_003179; LLI_112160; LLI_150344; . .

. . . . . .

Representing Cases with Normalized Legal Issues

For example, two cases “United States v. Kelly, 592 F.3d 586” and “Mewbourn v. State, 570 So. 2d 805” have these three Legal Issues in common:

“Under the automobile exception to the usual warrant requirement, law enforcement officers may search a vehicle without a warrant if it is readily mobile and probable cause exists to believe it contains contraband.”

“The probable cause standard does not require officials to possess an airtight case before taking action.”

“ . . . In general, the automobile exception to the warrant requirement is premised upon the exigencies associated with the mobility of a vehicle and the diminished expectation of privacy with regard to a vehicle.”

. . . . . .

Legal experts may find this higher degree of sharing of Issues as an indication of two cases sharing similar Factual Patterns, similar Argument Strategies, or both

A Recommendation System based on this kind of analogy could bring in similar cases that regular Systems would not be able to do

Representing Cases with Normalized Legal Issues

Linguistic Units occur in large Text Corpora, and form Networks among themselves. These Networks are Semantic by nature, and reflect relations between the Units

This kind of networks can be extracted from the Text Corpus to represent “knowledge” of the given domain

When the Knowledge Network is built with Legal Issues, much of the more profound legal knowledge that has not been explicit or easily seen will be revealed and become obvious

As Issues represent legal opinions or principles, the Legal Issue Network can be seen as a representation of Law to support various kinds of legal studies or research

The following is an example network from a small set of data


In the network, Issue of “Definition of Robbery” (CL_17) is properly linked to other Issues (as weighed by associations between nodes)


The Issue “Court’s duty to instruct on the lesser” (CL_147) has a stronger connection to “required reversal or resolution when error is made with that respect” (CL_264)

( Please see more analysis in the Paper )

Further Research

Study of the outcome of the automatic mining is in the plan for ways to better organize and merge very close Issues

Explore potentials of the network structure in support of research in Law

Thank You