yoshio. on nary relations

12
8/11/2019 YOSHIO. on Nary Relations http://slidepdf.com/reader/full/yoshio-on-nary-relations 1/12 On Nary Relations This documnent describes my ideas on the way to represent Nary Realtions in RDF. Table of contents:  Nary Relations Trinary Cases Unary Cases Binary Cases Cuasal relathionship Discussion on reification and uncertainty On patterns in the WD from SWBPDWG Nary Relations The basic relationship we can describe with RDF is binary, namely a relathionship between two resources. However, there are many cases that we want to express the relationship among more than 2 resources. And there have been discussions and proposals for the framework for the description of those Nary relathionships (see  NaryRelations page in ESW Wiki for example) And RDF Best Practice and Deployment WG has published its working draft Defining N-ary Relations on the Semantic Web: Use With Individuals. This page presents my (ongoing) proposal for a framework for presenting N-ary relationships. It looks similar to the "Pattern 2" analysis in the working note, but more generalized to include "unary" and "binary" case, and basic vocabulary is proposed here(@@they appear in examples, but yet to be defined formally) This approach owes its most part to the approaches in linguistics. go to the top of this page Trinary Cases Dative expression Example: John teaches math to Mary. [ a :teach;  role:agent :John;

Upload: chyleno3791

Post on 02-Jun-2018

229 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 1/12

On Nary Relations

This documnent describes my ideas on the way to represent Nary Realtions in RDF.

Table of contents:

 Nary Relations

Trinary Cases

Unary Cases

Binary Cases

Cuasal relathionship

Discussion on reification and uncertaintyOn patterns in the WD from SWBPDWG

Nary Relations

The basic relationship we can describe with RDF is binary, namely a relathionship between two resources.

However, there are many cases that we want to express the relationship among more than 2 resources. And therehave been discussions and proposals for the framework for the description of those Nary relathionships (see

 NaryRelations page in ESW Wiki for example)

And RDF Best Practice and Deployment WG has published its working draft Defining N-ary Relations on the

Semantic Web: Use With Individuals.

This page presents my (ongoing) proposal for a framework for presenting N-ary relationships.

It looks similar to the "Pattern 2" analysis in the working note, but more generalized to include "unary" and "binary"

case, and basic vocabulary is proposed here(@@they appear in examples, but yet to be defined formally)

This approach owes its most part to the approaches in linguistics.

↑go to the top of this page

Trinary Cases

Dative expression

Example:

John teaches math to Mary.

[ a :teach;

  role:agent :John;

Page 2: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 2/12

  role:thme :Math;

  role:goal :Mary

].

Actually the analysis is the same as that of "John teaches Mary math."

↑go to the top of this page

Unary Cases

Agentive subject

Example: "John swims."

[ a :swim;

  role:agent John ].

Thematic subject

Page 3: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 3/12

Example:

"Titanic sank."

 

[ a :sank;

  role:theme :Titanic ].

 

or 

 

[ a :sink;

  role:theme :Titanic;

  role:tense role:past

 ].

 

↑go to the top of this page

Binary Cases

Page 4: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 4/12

By generalizing the "Predicate as the main node" approach above to the trinary and unary cases, we get somewhat

new (or unfamiliar) graphs for conventional binary relations.

 Namely, even in expressing binary relationship, we make a node representing the (instance of) main predicate, and

connect each arguments to that node.

This approach is similar to reification, but different in that the "main" node is not of type rdf:Statement, but of the

seamantic predicate (so we don't have arcs labeled rdf:predicate) . And labels attatched to the arcs are not

syntax labels likerdf:subject or rdf:object, but semantic ones ( thematic roles aka θ roles).

Agent, Theme

Example:

John teaches math.

[ a :teach;

  role:agent :John;

  role:theme :Math].

 

Agent, Location

Example:

John swims in the pool.

[ a :swim;

  role:agent :John;

  role:location :Pool

].

 

Page 5: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 5/12

Or 

[ a :swim;

  role:agent :John;  role:location [ a :in;

  role:theme]

].

 

↑go to the top of this page

Cuasal relationship

Something causes something

Let's begin with a very simple case.

Example:

Smoking causes lung cancer.

Page 6: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 6/12

[ a :cause;

  role:source :smoking;

  role:theme :lung_cancer

].

Something cuases someone to do something

Example:

John made Mary meet Sarah.

[ a :made;  role:agent :John;

  role:theme [ a :meet;

  role:experiencer :Mary;

  role:theme :Sarah

  ]

].

Page 7: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 7/12

Some event causes someone to do something

Example:

That John died made Mary refrain from smoking.

[ a :made;

  role:source [a :died;  role:theme :John];

  role:theme [a :refrain_from;

  role:agent :Mary;

  role:source :smoking]

]

↑go to the top of this page

Discussion on reification and uncertainty

What's the problem? an example and an analysis

When adopting analysis above, do we have any problems with reification?

When doing reification as usual, the resultant graph seems a little bit complicated.

For example, consider "John teaches math.", of which our analysis was

[ a :teach;

  role:agent :John;

  role:theme :Math

].

 

Page 8: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 8/12

When we apply reification to that graph, the result would be

_:b2 a rdf:Statement;  rdf:subject _:b1;

  rdf:predicate role:agent;

  rdf:object :John.

_:b3 a rdf:Statement;

  rdf:subject _:b1;

  rdf:predicate role:theme;

  rdf:object :Math.

_:b1 a :teach.

 

Does this seem problematic? → At first glance, yes. It's too much complicated.

However, the sentence above actually (simulutanously) says these two things:

It is John who teachs math.and

It is math that John teachs.

So, it is natural that we have two reified triples.

Page 9: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 9/12

And we can attach our belief to either of them. For example, we can say "It is 75% probable that it is John who

teaches math." with

_:b4 a prob:Belief;

  prob:proposition _:b2;

  prob:has_probability [a prob:probability;

  rdf:value "0.75"].

Another analysis

Actually, there could be another analysis: a more complicated/sofisticated version. In the analysis above, we

didn't reify the statement ":b1 a rdf:type", but we can also reify it.

So, the reified version is:

_:b2 a rdf:Statement;

  rdf:subject _:b1;

  rdf:predicate role:agent;  rdf:object :John.

_:b3 a rdf:Statement;

  rdf:subject _:b1;

  rdf:predicate role:theme;

  rdf:object :Math.

_:b4 a rdf:Statement;

  rdf:subject _:b1;

  rdf:predicate rdf:type;

  rdf:object :teach.

 

Page 10: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 10/12

What does this mean? It means "It is to teach (not to study, for example) that John does with math." (I'm not

sure if it's correct English senence, though)

↑go to the top of this page

On patterns in the WD from SWBPDWG

Christine has breast tumor with high probability.

[ a prob:Belief;

  prob:proposition [ a :have;

  role:location :Christine;

  role:theme [ a :breast_tumor]

  ];

  prob:has_probability _:b1

].

_:b1[ a prob:probability].

_:b2[ a :high;

  role:theme _:b1].

Page 11: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 11/12

Steve has temperature, which is high, but falling

[ a :have;

  role:location :Steve;

  role:theme _:b1

].

_:b1 a :temparature.

[ a :high;

  role:theme _:b1

].

[ a :falling;

  role:theme _:b1

].

John buys a "Lenny the Lion" book from book.example.com for $15 as abirthday gift.

[ a :buy;

  role:agent :John;

  role:theme [ a :Lenny_the_lion_book];

  role:source :books_example_com;

  role:instrument "$15";

  role:purpose :birthday_gift

].

Page 12: YOSHIO. on Nary Relations

8/11/2019 YOSHIO. on Nary Relations

http://slidepdf.com/reader/full/yoshio-on-nary-relations 12/12

↑go to the top of this page

Created by Yoshio Fukushige

 [email protected]