NED with two-stage coherence optimization

Filip Ilievski, Marieke van Erp, Piek Vossen, Wouter Beek & Stefan Schlobach

or

How I am teaching my bottle of Jack Daniel’s not to turn into a 168-years-old person with a net income of $120.000.000

Context

... is being persistently avoided when processing language by machines. No wonder. The context

is hard to quantify.

but the context lies in the basis of the human communication!

The burden of context in language

● The language is context-dependent● Verbal context

○ Ford fell from a tree.■ What is “Ford” ?

● Social context○ What is “2+2” ?

■ In mathematics it is 4■ In the car domain it is a car configuration: 2 front + 2

back seats■ In psychology it is a family with 2 parents and 2 children

Lincoln increased the annual vehicle sales to 300.000.y was born in Lincoln.Lincoln fell from a tree.Lincoln was standing on the shelf. It was covered in leather.

Shallow processing

Motivation

The shallow approaches can do only this much.Claim #1: we need to deepen the processing.Claim #2: context is a limitless inspiration

- verbal- social- domain

- spatial- temporal- discourse

- (you-name-it)

Shall we go a step further?

How to go about it

Combine many pieces (algorithms) in a puzzle (solution)Use as extensive and global knowledge as possible:

Semantic WebNatural Language Processing Lexical resources

Approach

Optimize the semantic coherence of the disambiguated entities, while still excluding the verbally incorrect options and skewing towards the domain and the popularity of the entities.

Components

- Verb-based knowledge from NLP, VerbNet, FrameNet and a domain ontology

- Domain skew (based on corpus analysis)- Popularity of the candidates (from DBpedia)- Semantic connectivity and similarity (based on DBpedia

information)

No module or knowledge source is perfect,but >1 of both will be helpful !

System design

The background knowledge

Data

Annotated WikiNews articles3 subcorpora:- Airbus Boeing (30)- General Motors (30)- Stock Market (30)

Results

FrameNet+Domain ontology filterAirbus GM Stock market

# links filtered 3 21 22

# incorrect links filtered

3 13 19

# correct links filtered

0 0 3

# not in GS filtered

0 8 0

“Trading on Russia’s stock markets ...”predicate: markets, Commerce_sell@Seller: Russia

Combinations

Conclusions

Context is usefulSemantic Web can help to model background knowledge

We are still finding new puzzle pieces

Thank You !

Appendices

Future

Get rid of the boring pipeline approach.Use full-blown optimization system!

Resources

Grammatical structure and meaning of words Background knowledgeStructured linguistic

information

Semantic WebNatural Language Processing Lexical resources

Example

“The United States transferred six detainees from the Guantánamo Bay prison to Uruguay this weekend, the Defense Department announced early Sunday.”

State-of-the-art: United States Guantanamo Bay Uruguay Defence Department

Geographical region GB detention camp Geographical region US Dept. of Defence

Fed. Government Place Football team Ministry of Defence of Rep. of Korea

Men’s soccer team The naval base River

Women’s soccer team Battle of GB Rugby union team

Rugby union team U20 football team

Men’s ice hockey team U17 football team

Men’s basketball team

Secondary education in US

VN: send-11.1

transferred

A0 is Animate or OrganizationA0:United States

United States is Animate or Organization

∏

A1: from Guantanamo Bay

A2: to Uruguay

A1 is Location

A2 is Location

Guantanamo Bay is a location Uruguay is a location

VN: say-37.7

announced

A0 is Animate or OrganizationA0:the Defence Department

∏

The Defence Department is an Animate or an Organization

After VerbNetUnited States Guantanamo Bay Uruguay Defence Department

Geographical region GB detention camp Geographical region US Dept. of Defence

Fed. Government Place Football team Ministry of Defence of Rep. of Korea

Men’s soccer team The naval base River

Women’s soccer team Battle of GB Rugby union team

Rugby union team U20 football team

Men’s ice hockey team U17 football team

Men’s basketball team

Secondary education in US

Results

VN: send-11.1

transferred

A0 is Animate or OrganizationA0:United States

United States is Animate or Organization

∏

A1: from Guantanamo Bay

A2: to Uruguay

A1 is Location

A2 is Location

Guantanamo Bay is a location Uruguay is a location

VN: say-37.7

announced

A0 is Animate or OrganizationA0:the Defence Department

∏

The Defence Department is an Animate or an Organization

After VerbNetUnited States Guantanamo Bay Uruguay Defence Department

Geographical region GB detention camp Geographical region US Dept. of Defence

Fed. Government Place Football team Ministry of Defence of Rep. of Korea

Men’s soccer team The naval base River

Women’s soccer team Battle of GB Rugby union team

Rugby union team U20 football team

Men’s ice hockey team U17 football team

Men’s basketball team

Secondary education in US