Argument
Extrac.on
from
Social
Media
Using
GATE
Adam
Wyner
Compu.ng
Science,
University
of
Aberdeen
Summer
...
Goals
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• Iden.fy
materials
(social
m...
Materials
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
3
Where
Arguments
Appear
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
4
• Consumer...
Current
Events
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• ScoZsh
Independence...
ScoZsh
Independence
2014
The
issue
of
what
currency
an
independent
Scotland
would
use
has
become
the
key
...
Arguments
in
debategraph.org
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
Current...
Consumer
Comments
on
Amazon
Argumenta.on
Summer
School,
Dundee
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A.
Wyner,
Univ
of
Aberdeen
8
Pro
and
Con
Argumenta.on
Summer
School,
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A.
Wyner,
Univ
of
Aberdeen
9
Comments
on
Comments
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
10
Policy
Consulta.ons
-­‐
LIBER
on
Copyright
-­‐
Ques;on
9.
Should
the
law
be
clarified
with
respect
to
whe...
What
Needs
to
be
Done?
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• Annotate ...
Generically
What
Needs
to
be
Done?
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen...
What
Needs
to
be
Done?
Basic
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
14
...
What
Needs
to
be
Done?
Ques.ons
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
•...
What
Needs
to
be
Done?
Scramble
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
1...
Scramble
in
Comment
Update
Argumenta.on
Summer
School,
Dundee
nada
dnana
a
kkkd
andai
;a.
n=jja
nmae
a;kda...
Scrambling
Ques.ons
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• How
do
we
kn...
Generic
Issues
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• Reconstruc.on
of
a...
Argument
Pipeline
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
20
Loca.ng
the
Problem
and
Engineering
a
Solu.on
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
...
Three
Stages
Graph
–
Structured
or
Instan.ated
AFs
gOkZI[jjQ][
gZIq]gX
Argumenta.on
Summer
School,
Dundee
07...
hI rjI[hQ][h]N
gOkZI[jh
rjI[hQ][h]N
][EYkhQ][h
/jIdE][hjgkEj
gOkZI[jh[GjjEXh
/jIdÏQGI[jQNshIjh]N
EEIdjIGgOkZI[j...
Logic-­‐based
Instan.ated
Argumenta.on
Besnard
and
Hunter
Argumenta.on
Summer
School,
Dundee
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A.
Wyn...
Abstract
Argumenta.on
Argumenta.on
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Dundee
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Wyner,
Univ
of
Aberdeen
24
Preferred
...
Zeroing
In
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
Source
text
Knowledge
b...
Context
with
Respect
to
Analysis
and
Argumenta.on
Schemes
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
W...
Current
Tools
to
Extract
and
Structure
Arguments
from
Text
Argumenta.on
Summer
School,
Dundee
07/09/2014
A. ...
Argumenta.on
Schemes
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• Pa[erns
of
p...
Overall
Proposal
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• Normalise
natural...
Caveat
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• Low
level
automa.on,
using...
Normalise
for
Argumenta.on
Schemes
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
...
Annotate
–
Query
–
Extract
Argumenta.on
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Wyner,
Univ
of
Aberdeen
32
• A...
Language
Issues
Argumenta.on
Summer
School,
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Wyner,
Univ
of
Aberdeen
33
Problems
with
Language
I
• Iden.fica.on,
implicit
informa.on,
mul.ple
forms
with
the
same
meaning,
the
same ...
Problems
with
Language
II
• Concepts,
dispersed
meanings,
rules,
diathesis:
• Plain.ff,
judge,
a[orney.
• Jane...
Problems
with
Language
III
• Ambiguity,
vagueness,
underspecifica.on:
• The
man
saw
the
woman
with
binoculars...
Problems
with
Language
IV
• Complexity,
length,
and
layout
(see
our
Camera
example).
• Intersenten.al
connec....
Problems
for
Annota.on
• Annotate
large
legacy
corpora.
• Address
growth
of
corpora.
• Reduce
number
of
huma...
Addressing
the
Problems
• Decompose
big
problems
down
to
smaller
problems.
• Modularise
problems.
• Address
t...
Methodology
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
40
Approaches
• Knowledge
light
in
terms
of
knowledge
of
the
domain
or
of
language
–
sta.s.cal
or
machine
le...
Overall
Approach
• Decompose
large
complex
problems
into
smaller,
manageable
problems
for
which
we
can
creat...
Development
Caveat
• Developing
working
prototypes
(much
less
public
and/or
commercial
tools)
takes
resources....
Development
Cycle
Source
Text
Linguis.c
Analysis
Tool
Construc.on
Evalua.on
Knowledge
Extrac.on
Argumenta.on
S...
Whazza
Methodology?
07/09/2014
Argumenta.on
Summer
School,
Dundee
A.
Wyner,
Univ
of
Aberdeen
45
Linguis.c
Processing
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
46
Computa.onal
Linguis.c
Cascade
I
• Sentence
segmenta.on
-­‐
divide
text
into
sentences.
• Tokenisa.on
-­‐
wor...
Computa.onal
Linguis.c
Cascade
II
• Dependency
analysis
–
sentence
subject,
subordinate
clauses,
pronominal
an...
Overall
Processing
Strategy
• Make
implicit
informa.on
explicit
by
adding
machine
readable
annota7ons.
Argumen...
A
Tool
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
50
GATE
• General
Architecture
for
Text
Engineering
(GATE)
-­‐
open
source
framework
which
supports
plug-­‐in
N...
GATE
Benefits
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
52
• No
need
for
pa...
GATE
Basic
Process
Flow
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
53
Can
ad...
GATE
-­‐
Gaze[eers
• Gaze[eers
are
lookup
lists
that
add
features
-­‐
when
a
string
in
the
text
is
locat...
GATE
–
JAPE
Rules
• JAPE
Rules
(finite
state
transduc.on
rules)
create
overt
annota.ons
and
reuse
other
an...
GATE
–
Building
an
Applica.on
• Have
Gaze[eer
lists
and
JAPE
rules
for:
• lists
in
various
forms;
• excep....
Example
-­‐
Camera
Argumenta.on
Summer
School,
Dundee
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A.
Wyner,
Univ
of
Aberdeen
57
Argument
Fragment
for
a
Camera
Argumenta.on
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School,
Dundee
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Wyner,
Univ
of
Aberdeen
58
Pro
and
Con
Argumenta.on
Summer
School,
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Wyner,
Univ
of
Aberdeen
59
Comments
on
Comments
Argumenta.on
Summer
School,
Dundee
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A.
Wyner,
Univ
of
Aberdeen
60
Goals
• Extract
arguments
distributed
across
a
corpora
and
evaluate
them
with
formal,
automated
tools.
• Spe...
Consumer
Argumenta.on
Scheme
Variables
in
schemes
as
targets
for
extrac7on.
Premises:
• Camera
X
has
propert...
Analyst’s
Goal:
Instan.ate
Premises:
• The
Canon
SX220
has
good
video
quality.
• Good
video
quality
promotes...
Annota.ng
Text
• Annotate
text:
– Simple
or
complex
annota.ons.
– Highlight
annota.ons
with
– Search
for
and ...
To
Find
Argument
Passages
• Use:
– Indicators
of
aJer,
as,
because,
for,
since,
when,
....
– Indicators
of ...
Rhetorical
Terminology
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
66
To
Find
What
is
Being
Discussed
• Use
:
– Has
a
flash
– Number
of
megapixels
– Scope
of
the
zoom
– Lens ...
Domain
Terminology
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
68
To
Find
A[acks
Between
Arguments
• Use
contrast
terminology:
– Indicators
but,
except,
not,
never,
no,
.... ...
Sen.ment
Terminology
Argumenta.on
Summer
School,
Dundee
07/09/2014
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Wyner,
Univ
of
Aberdeen
70
,
,
Argumenta.on
Summer
School,
Dundee
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A.
Wyner,
Univ
of
Aberdeen
71
Query
for
Pa[erns
Argumenta.on
Summer
School,
Dundee
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A.
Wyner,
Univ
of
Aberdeen
72
An
Argument
for
Buying
the
Camera
Premises:
The
pictures
are
perfectly
exposed.
The
pictures
are
well-­‐foc...
An
Argument
for
NOT
Buying
the
Camera
Premises:
The
colour
is
poor
when
using
the
flash.
The
images
are ...
Counterarguments
to
the
Premises
of
“Don’t
buy”
The
colour
is
poor
when
using
the
flash.
For
good
colour,...
In
More
Detail
Argumenta.on
Summer
School,
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Wyner,
Univ
of
Aberdeen
76
Argumenta.on
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Univ
of
Aberdeen
77
Argumenta.on
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Wyner,
Univ
of
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78
Argumenta.on
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Univ
of
Aberdeen
79
Argumenta.on
Summer
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Wyner,
Univ
of
Aberdeen
80
Argumenta.on
Summer
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Wyner,
Univ
of
Aberdeen
81
Argumenta.on
Summer
School,
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Wyner,
Univ
of
Aberdeen
82
Argumenta.on
Summer
School,
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Wyner,
Univ
of
Aberdeen
83
Argumenta.on
Summer
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Wyner,
Univ
of
Aberdeen
84
Argumenta.on
Summer
School,
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Wyner,
Univ
of
Aberdeen
85
Argumenta.on
Summer
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Wyner,
Univ
of
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86
Argumenta.on
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Univ
of
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Argumenta.on
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Univ
of
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Argumenta.on
Summer
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Wyner,
Univ
of
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ANNIC
Movie
Argumenta.on
Summer
School,
Dundee
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A.
Wyner,
Univ
of
Aberdeen
90
Example
-­‐
Rules
• Rule
iden.fica.on
in
regula.ons;
what
one
can
'argue'
for
and
against.
• Using
previous...
Sample
Outputs
Consequence,
list
structure,
and
conjuncts
of
the
antecedent.
Excep.on,
agent
NP,
deon.c
conc...
Sample
Output
Theme,
deon.c
modal,
passive
verb,
agent
with
complex
rela.ve
clause.
07/09/2014
Argumenta.on
...
Sample
Output
-­‐
Overall
07/09/2014
Argumenta.on
Summer
School,
Dundee
A.
Wyner,
Univ
of
Aberdeen
94
Sample
Output
-­‐
XML
07/09/2014
Argumenta.on
Summer
School,
Dundee
A.
Wyner,
Univ
of
Aberdeen
95
This
is ...
Sample
Output
–
ANNIC
Search
07/09/2014
Argumenta.on
Summer
School,
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Wyner,
Univ
of
Aberdeen
96
Gold
Standards
Argumenta.on
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School,
Dundee
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Wyner,
Univ
of
Aberdeen
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Teamware
to
Create
Gold
Standards
07/09/2014
Argumenta.on
Summer
School,
Dundee
A.
Wyner,
Univ
of
Aberdeen
...
Results
of
Annota.on
• The
annotators
carry
out
their
task
and
complete
the
project.
• Carry
out
inter-­‐an...
Addi.ons
Argumenta.on
Summer
School,
Dundee
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A.
Wyner,
Univ
of
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100
Add
to
Explorer
(or
Teamware)
• Verbs
for
proposi.onal
aZtudes,
e.g.
believe,
know,
hope
and
speech
acts,
...
References
Argumenta.on
Summer
School,
Dundee
07/09/2014
A.
Wyner,
Univ
of
Aberdeen
• Wyner,
van
Engers,
Hun...
of 103

Natural Language Processing of Argumentation. Adam Wyner. Summer School Lecture 2014

Adam Wyner's presentation on natural language processing of argumentation such as found in social media, newspapers, and law. Relevant to semantic web, text analysis, computational linguistics, argumentation. University of Aberdeen.
Published on: Mar 3, 2016
Published in: Science      
Source: www.slideshare.net


Transcripts - Natural Language Processing of Argumentation. Adam Wyner. Summer School Lecture 2014

  • 1. Argument Extrac.on from Social Media Using GATE Adam Wyner Compu.ng Science, University of Aberdeen Summer School on Argumenta.on: Computa.onal and Linguis.c Perspec.ves University of Dundee Sept. 7, 2014
  • 2. Goals Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • Iden.fy materials (social media) and generic issues. • Outline linguis.c issues. • Outline GATE methodology. • Provide some examples. 2
  • 3. Materials Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 3
  • 4. Where Arguments Appear Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 4 • Consumer websites: Amazon, eBay,... • Law: policy making, Supreme Court transcripts, case based reasoning, regula.ons. • BBC's Have Your Say and Moral Maze. • Medical diagnosis. • Current events. • Making plans. • Debatepedia, Wikipedia, mee.ng annota.ons, web-­‐forums,... • Social media: Facebook, da.ng
  • 5. Current Events Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • ScoZsh Independence and Currency • h[p://www.bbc.co.uk/news/uk-­‐scotland-­‐scotland-­‐ poli.cs-­‐2622589 5
  • 6. ScoZsh Independence 2014 The issue of what currency an independent Scotland would use has become the key ba[leground of the referendum debate. The ScoZsh government is in favour of a sterling zone, saying it would be in the interests of both Scotland and the UK to con.nue to formally share the pound if the former votes for independence, ensuring stability for both states. UK chancellor George Osborne has said the UK would not enter into a currency union with Scotland if it voted 'Yes' in September's referendum, claiming such a union would be against the economic interests of England, Wales and Northern Ireland. Mr Osborne's statement was the UK government's strongest interven.on in the debate yet, and his posi.on was supported by both Labour and the Liberal Democrats. First Minister Alex Salmond countered Mr Osborne's claims in a speech to pro-­‐independence business leaders in Aberdeen on Monday, which he said had "deconstructed" the case against a currency union. So what are Mr Osborne's key arguments and how has Mr Salmond sought to counter them? Claim: Trade with Scotland is important to the UK, but the overall propor;on is small George Osborne: "I'm the first to say that our deeply integrated businesses and their suppliers are compelling reasons for keeping the UK together -­‐ 70% of ScoZsh trade is with the rest of the UK. That is a massive propor.on. "And trade with Scotland is important to the rest of the UK -­‐ but at only 10% of the total trade, it is a much smaller propor.on. These trade figures don't make the unanswerable case for a shared currency that the ScoZsh government assume." Alex Salmond: "I am publishing an es.mate of the transac.ons costs he would poten.ally impose on businesses in the rest of the UK. They run to many hundreds of millions of pounds. My submission is that this charge -­‐ let us call it the George tax -­‐ would be impossible to sell to English business. "In fact if you remove oil and gas from the equa.on, Scotland is one of the very few countries in the world with which England has a balance of trade surplus." Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 6
  • 7. Arguments in debategraph.org Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen Current Method -­‐ read text -­‐ manually analyse -­‐ manually enter text into tool -­‐ manually annotate. Problems -­‐ slow, costly, error-­‐ prone, ad hoc, must search for 'place' of new addi.ons, etc.... 7
  • 8. Consumer Comments on Amazon Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 8
  • 9. Pro and Con Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 9
  • 10. Comments on Comments Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 10
  • 11. Policy Consulta.ons -­‐ LIBER on Copyright -­‐ Ques;on 9. Should the law be clarified with respect to whether the scanning of works held in libraries for the purpose of making their content searchable on the Internet goes beyond the scope of current excep;ons to copyright? -­‐ Yes. -­‐ Not all the material digi.sed by publishers is scanned with OCR (Op.cal Character Recogni.on) with the purpose of making the resul.ng content searchable. If the rights holders will not do this, libraries should be able to offer this service. It would have a transforma.ve effect on research, learning and teaching by opening up a mass of content to users which can be searched using search engines. The interests of copyright holders will not be harmed, because the resul.ng output will act as marke.ng material for their materials. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 11
  • 12. What Needs to be Done? Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • Annotate textual passages for argument relevant por.ons (premise, claim) • Annotate rela.ons amongst passages (premise of what argument) • Represent in some machine readable form. • Thought experiments to objec7fy and abstract the issues. 12
  • 13. Generically What Needs to be Done? Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 13
  • 14. What Needs to be Done? Basic Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 14 andalka nadlka fa adlkaa la lkd alkdj a a akj dal;k fda ada. a;lkd a andalkda anda;k a jad ie ae. a;lkd. nainea ; alkei nai lalin oa nekn. ake anoiiena dk aieane0-­‐a an a;kl aeu ajena. ;oi anoi alkd ao;na oen oiana oin. l ;kja dka j ajda djflka kle ak kad la ien ae n en. lkj ad ad fa ;adja dfakd. Source Text A a1.p.1. -­‐ andalka nadlka fa adlkaa la lkd alkdj a a akj dal;k fda ada. a1.p.2. -­‐ a;lkd a andalkda anda;k a jad ie ae. a;lkd. a1.c. -­‐ nainea ; alkei nai lalin oa nekn. a2.p.1 -­‐ ake anoiiena dk aieane0-­‐a an a;kl aeu ajena. a2.p.1 -­‐ ;oi anoi alkd ao;na oen oiana oin. a2.e.3 -­‐ l ;kja dka j ajda djflka kle ak kad la ien ae n en. a1.c -­‐ lkj ad ad fa ;adja dfakd. Annotated Text A Key: premise, excep.on, claim
  • 15. What Needs to be Done? Ques.ons Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • How do we know (as readers) which is a premise, which is a claim, and which is an excep.on? – explicit linguis.c markers (e.g. assuming X, therefore Y) – order of sentences? – other, e.g. context? • If we scrambled the order of the sentences, could we recons.tute the argument annota.on? – Engineer – "Doesn't happen, not relevant. Build for par.culars." – Scien.st – "Does it happen? If it does or could, how do we address it? Explore for principles." 15
  • 16. What Needs to be Done? Scramble Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 16 andalka nadlka fa adlkaa la lkd alkdj a a akj dal;k fda ada. nainea ; alkei nai lalin oa nekn. a;lkd a andalkda anda;k a jad ie ae. a;lkd. ;oi anoi alkd ao;na oen oiana oin. lkj ad ad fa ;adja dfakd. l ;kja dka j ajda djflka kle ak kad la ien ae n en. ake anoiiena dk aieane0-­‐a an a;kl aeu ajena. Source Text A a1.p.1. -­‐ andalka nadlka fa adlkaa la lkd alkdj a a akj dal;k fda ada. a1.p.2. -­‐ a;lkd a andalkda anda;k a jad ie ae. a;lkd. a1.c. -­‐ nainea ; alkei nai lalin oa nekn. a2.p.1 -­‐ ake anoiiena dk aieane0-­‐a an a;kl aeu ajena. a2.p.1 -­‐ ;oi anoi alkd ao;na oen oiana oin. a2.e.3 -­‐ l ;kja dka j ajda djflka kle ak kad la ien ae n en. a1.c -­‐ lkj ad ad fa ;adja dfakd. Annotated Text A Key: premise, excep.on, claim
  • 17. Scramble in Comment Update Argumenta.on Summer School, Dundee nada dnana a kkkd andai ;a. n=jja nmae a;kda nIanl. 07/09/2014 A. Wyner, Univ of Aberdeen 17 andalka nadlka fa adlkaa la lkd alkdj a a akj dal;k fda ada. a;lkd a andalkda anda;k a jad ie ae. a;lkd. nainea ; alkei nai lalin oa nekn. Source Text A a1.p.1. -­‐ andalka nadlka fa adlkaa la lkd alkdj a a akj dal;k fda ada. a1.p.2. -­‐ a;lkd a andalkda anda;k a jad ie ae. a;lkd. a1.p.3. -­‐ n=jja nmae a;kda nIanl. a1.e.2. -­‐ nada dnana a kkkd andai ;a. a1.c. -­‐ nainea ; alkei nai lalin oa nekn. Annotated Text A plus Key: premise, excep.on, claim Source Text B Source Text C a;lkd a andalkda likalaka anda;k a jad ie ae. a;lkd. (contrary to a1.p.2) Source Text D
  • 18. Scrambling Ques.ons Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • How do we know when two premises are/are not the same? • How do we know what argument to a[ach a proposi.on to? • Addressing these ques.ons may require some deep syntac.c and seman.c analysis (hint, I think it does and can be done....eventually). • BUT VERY HARD!! • Find a less demanding, near term approach towards similar objec.ves. 18
  • 19. Generic Issues Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • Reconstruc.on of arguments from textual sources: – extrac.on for argument evalua.on. – Discon.nuity of arguments in textual source. – Knowledge base construc.on and dynamics. • Linguis.c issues: – Domain terminology. – Linguis.c informa.on and variety (many-­‐to-­‐one sentence-­‐ proposi.on). – Argument rela.ons (premise, claim, excep.on, contrary). – Sources of defeasibility (epistemic 'strength'). – Other argument component, e.g. proposi.onal aZtudes (e.g believe, know), speech act verbs (e.g. assert, grant). 19
  • 20. Argument Pipeline Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 20
  • 21. Loca.ng the Problem and Engineering a Solu.on Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 21 • The knowledge acquisi.on bo[leneck from NL to some formal representa.on. • Rela.onship to other parts of the argumenta7on processing pipeline.
  • 22. Three Stages Graph – Structured or Instan.ated AFs gOkZI[jjQ][ gZIq]gX Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 22 []qYIGOI
  • 23. hI rjI[hQ][h]N gOkZI[jh rjI[hQ][h]N ][EYkhQ][h /jIdE][hjgkEj gOkZI[jh[GjjEXh /jIdÏQGI[jQNshIjh]N EEIdjIGgOkZI[jh /jIdďQGI[jQNshIjh]N EEIdjIGE][EYkhQ][h Three Stages -­‐ Caminada and Wu 2011 Knowledge Acquisi.on Bo[leneck: .me, labour, exper.se to construct a KB at scale.
  • 24. Logic-­‐based Instan.ated Argumenta.on Besnard and Hunter Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 23 • An argument is an ordered pair ψ, α; ψ is a subset of a given KB and α is an atomic proposi.on from the KB; ψ is a minimal set of formulae such that ψ implies α, and ψ does not imply a contradic.on. ψ is said to support the claim α. • Where p and q are atoms, and where the KB is comprised of p and p→q, then {p, p→q}, q is an argument. • We could have a KB from which we can form an argument which supports ¬q, {p, p→¬q}, ¬q. In addi.on and with respect to this argument, suppose we can form an undercuer {r, r→¬p}, ¬p and a rebual {r, r→¬p, ¬p→q}, q}. • KBs (even rela.vely small ones) generate lots of arguments and a[ack rela.onships which can be structured in a tree.
  • 25. Abstract Argumenta.on Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 24 Preferred extension: {a, c, d, h, i, k}
  • 26. Zeroing In Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen Source text Knowledge base argumenta.on schemes Generated arguments (abstract or instan.ated). 25
  • 27. Context with Respect to Analysis and Argumenta.on Schemes Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 26
  • 28. Current Tools to Extract and Structure Arguments from Text Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 27 • Ra.onale, Araucaria, Carneades (Gordon 2007), IMPACT Project, Legal Appren.ce, Argument Wall,.... • Pale[e of annota.ons and templates. • All manual. No NLP.
  • 29. Argumenta.on Schemes Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • Pa[erns of presump.ve (defeasible) reasoning (Walton 1996) • Prac.cal Reasoning with values: – Do ac.on (transi.on) because: • Current circumstances -­‐ a list of literals. • Consequences – a list of literals. • Values (promoted, demoted, neutral wrt ac.ons) – a list of terms. • Credible Source: – Z is accepted because: • X is an expert in domain Y. • X stated literal Z • Z is about domain Y. 28
  • 30. Overall Proposal Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • Normalise natural language source material into argumenta.on schemes. • Formalise argumenta.on schemes in terms of roles of proposi.ons in the scheme and internal structure of proposi.ons (predicates and typed variables). • Connect argumenta.on schemes to abstract arguments. • Relate one scheme to another in terms of contrariness. • Extract scheme relevant informa.on from the source. • Create a knowledge base to instan.ate variables. 29
  • 31. Caveat Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • Low level automa.on, using high level structures as guides. • For example, no automa.c search for scheme filling, grounding of variables, contrast iden.fica.on. • Progress can be made on these (and for contrast iden.fica.on, there is significant work already). 30
  • 32. Normalise for Argumenta.on Schemes Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 31
  • 33. Annotate – Query – Extract Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 32 • Annotate with respect to Argumenta.on Schemes. – characteris.c terminology of the scheme. – generalise the terminology to cover varia.on. – dis.nguish domain from generic terminology. • Complex, flexible queries over the annota.ons. – Low level (atomic) and high level (molecular) construc.ons. – Interac.ve, semi-­‐automa.c. • Export to some machine readable format -­‐ XML.
  • 34. Language Issues Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 33
  • 35. Problems with Language I • Iden.fica.on, implicit informa.on, mul.ple forms with the same meaning, the same form with mul.ple meanings: • En.ty ID: Jane Smith, for plain.ff. • Rela.on ID: Edgar Wilson disclosed the formula to Mary Hays. • Bill drove the car into Phil at 60 MPH. (agent, instrument, killing) • Jane Smith, Jane R. Smith, Smith, A[orney Smith.... • Jane Smith in one case decision need not be the same Jane Smith in another case decision. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 34
  • 36. Problems with Language II • Concepts, dispersed meanings, rules, diathesis: • Plain.ff, judge, a[orney. • Jane Smith represented Jones Inc. She is a partner at Dewey, Chetum, and Howe. To contact her, write to j.smith@dch.com. • If a woman is over 62 years old and lives in the UK, she is a pensioner. • Diathesis: alterna.ve sentence forms with (almost) synonymous meaning: Bill pushed Jill; Jill was pushed by Bill. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 35
  • 37. Problems with Language III • Ambiguity, vagueness, underspecifica.on: • The man saw the woman with binoculars. • It is illegal to leave a heap of shoes on the sidewalk. • Vehicles may not be driven in the park. • Sarcasm, irony. • Interpreta.on. • Context dependence, subjec.vity, arbitrary meaning, when I was at school, I know language.... Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 36
  • 38. Problems with Language IV • Complexity, length, and layout (see our Camera example). • Intersenten.al connec.ons: • Bill le the house. He drove home. • Bill le the house. He didn't feel comfortable there. • Bill le the house. It was an old house, once owned by a wealthy merchant. • Synonymy, antonyms, meronyms (finger part of hand), etc. • Repe..on. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 37
  • 39. Problems for Annota.on • Annotate large legacy corpora. • Address growth of corpora. • Reduce number of human annotators and tedious work. • Make annota.on systema.c, automa.c, and consistent. • Annotate fine-­‐grained informa.on: • Names, loca.ons, addresses, web links, organisa.ons, ac.ons, argument structures, rela.ons between en..es. • Map from well-­‐draed documents in NL to RDF/OWL/XML. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 38
  • 40. Addressing the Problems • Decompose big problems down to smaller problems. • Modularise problems. • Address the smaller, modular problems. • Compose solu.ons from parts. • Iden.fy (set aside, address, assign to someone else) remaining and/or highly problema.c issues. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 39
  • 41. Methodology Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 40
  • 42. Approaches • Knowledge light in terms of knowledge of the domain or of language – sta.s.cal or machine learning approaches. Algorithmically compare and contrast large bodies of textual data, iden.fying regulari.es and similari.es. Sparse data problem. Need a ‘gold standard’. No rules extracted. Opaque. Hard to modify. • Knowledge heavy in terms of lists, rules, and processes. Labour and knowledge intensive. Creates gold standards. Transparent. Can jus.fy outcomes. Can 'correct' solu.ons. • Can do either. Where textual traceability (jus.fica.on) is essen.al, knowledge heavy is important. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 41
  • 43. Overall Approach • Decompose large complex problems into smaller, manageable problems for which we can create solu.ons. • Soware engineering approach. • Papers by Wyner and Peters (2010, 2011). Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 42
  • 44. Development Caveat • Developing working prototypes (much less public and/or commercial tools) takes resources. • Tool development • Corpus development • Language analysis • It is a slow, painstaking, and gradual process of construc.ng modules to do the small tasks you need to build the large applica.ons you want. • Not a simple phone app. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 43
  • 45. Development Cycle Source Text Linguis.c Analysis Tool Construc.on Evalua.on Knowledge Extrac.on Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 44
  • 46. Whazza Methodology? 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 45
  • 47. Linguis.c Processing Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 46
  • 48. Computa.onal Linguis.c Cascade I • Sentence segmenta.on -­‐ divide text into sentences. • Tokenisa.on -­‐ words iden.fied by spaces between them. • Part of speech tagging -­‐ noun, verb, adjec.ve.... • Morphological analysis -­‐ singular/plural, tense, nominalisa.on, ... • Shallow syntac.c parsing/chunking -­‐ noun phrase, verb phrase, subordinate clause, .... • Named en.ty recogni.on -­‐ the en..es in the text. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 47
  • 49. Computa.onal Linguis.c Cascade II • Dependency analysis – sentence subject, subordinate clauses, pronominal anaphora,... • Rela.onship recogni.on – X is president of Y; A hit B with a car and killed B. • Enrichment -­‐ add lexical seman.c informa.on to verbs or nouns. • Supertagging – adding conceptual annota.ons to text. • Transla.on to logic for reasoning. • Each step guided by pa[ern matching and rule applica.on. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 48
  • 50. Overall Processing Strategy • Make implicit informa.on explicit by adding machine readable annota7ons. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 49
  • 51. A Tool Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 50
  • 52. GATE • General Architecture for Text Engineering (GATE) -­‐ open source framework which supports plug-­‐in NLP components to process a corpus of text. • GATE Training Courses h[ps://gate.ac.uk/ • A GUI to work with the tools. • A Java library to develop further applica.ons. • Components and sequences of processes, each process feeding the next in a “pipeline”. • Annotated text output or other sorts of output. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 51
  • 53. GATE Benefits Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 52 • No need for parsed, pre-­‐structured text. • Generic components apply anywhere. • No need for a gold standard. • Low entry point, no programming required. • Useful interface for analysis and demonstra.on. • Lots of public resources and open to build more add-­‐ons. • Connects to other tools, widely used....
  • 54. GATE Basic Process Flow Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 53 Can add further processing components to pipeline, e.g. NER, co-­‐reference, other other annota.ons,...
  • 55. GATE -­‐ Gaze[eers • Gaze[eers are lookup lists that add features -­‐ when a string in the text is located in a lookup list, annotate the string in the text with the feature. Conceptual covers. • Feature: list of items... • Obliga.on: ought, must, obliged, obliga.on.... • Excep.on: unless, except, but, apart from.... • Verbs according to thema.c roles: lists of verbs and their associated roles, e.g. run has an agent (Bill ran), rise has a theme (The wind blew). 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 54
  • 56. GATE – JAPE Rules • JAPE Rules (finite state transduc.on rules) create overt annota.ons and reuse other annota.ons (e.g. Parser Output): 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 55
  • 57. GATE – Building an Applica.on • Have Gaze[eer lists and JAPE rules for: • lists in various forms; • excep.on phrases in various forms; • condi.onals in various forms; • deon.c terms; • associa.ng gramma.cal roles (e.g. subject and object) with thema.c roles (agent and theme) in various forms. 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 56
  • 58. Example -­‐ Camera Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 57
  • 59. Argument Fragment for a Camera Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 58
  • 60. Pro and Con Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 59
  • 61. Comments on Comments Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 60
  • 62. Goals • Extract arguments distributed across a corpora and evaluate them with formal, automated tools. • Speed the work of human analysts. • Provide semi-­‐automa3c support. • Use aspects of NLP to incrementally address a range of problems (ambiguity, structure, contrasts,....) • Wyner, Schneider, Atkinson, and Bench-­‐Capon (2012). Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 61
  • 63. Consumer Argumenta.on Scheme Variables in schemes as targets for extrac7on. Premises: • Camera X has property P. • Property P promotes value V for agent A. Conclusion: • Agent A should Ac;on Camera X. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 62
  • 64. Analyst’s Goal: Instan.ate Premises: • The Canon SX220 has good video quality. • Good video quality promotes image quality for casual photographers. Conclusion: • Casual photographers should buy the Canon SX220. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 63
  • 65. Annota.ng Text • Annotate text: – Simple or complex annota.ons. – Highlight annota.ons with – Search for and extract text by annota.on. • GATE “General Architecture for Text Engineering”. – Works with large corpora of text. – Rule-­‐based or machine-­‐learning approaches. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 64
  • 66. To Find Argument Passages • Use: – Indicators of aJer, as, because, for, since, when, .... – Indicators of therefore, in conclusion, consequently, .... Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 65
  • 67. Rhetorical Terminology Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 66
  • 68. To Find What is Being Discussed • Use : – Has a flash – Number of megapixels – Scope of the zoom – Lens size – The warranty Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 67
  • 69. Domain Terminology Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 68
  • 70. To Find A[acks Between Arguments • Use contrast terminology: – Indicators but, except, not, never, no, .... – Contras.ng sen.ment The flash worked . The flash worked . Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 69
  • 71. Sen.ment Terminology Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 70
  • 72. , , Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 71
  • 73. Query for Pa[erns Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 72
  • 74. An Argument for Buying the Camera Premises: The pictures are perfectly exposed. The pictures are well-­‐focused. No camera shake. Good video quality. Each of these proper.es promotes image quality. Conclusion: (You, the reader,) should buy the CanonSX220. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 73
  • 75. An Argument for NOT Buying the Camera Premises: The colour is poor when using the flash. The images are not crisp when using the flash. The flash causes a shadow. Each of these proper.es demotes image quality. ! Conclusion: (You, the reader,) should not buy the CanonSX220. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 74
  • 76. Counterarguments to the Premises of “Don’t buy” The colour is poor when using the flash. For good colour, use the colour seZng, not the flash. The images are not crisp when using the flash. No need to use flash even in low light. The flash causes a shadow. There is a correc.ve video about the flash shadow. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 75
  • 77. In More Detail Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 76
  • 78. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 77
  • 79. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 78
  • 80. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 79
  • 81. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 80
  • 82. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 81
  • 83. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 82
  • 84. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 83
  • 85. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 84
  • 86. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 85
  • 87. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 86
  • 88. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 87
  • 89. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 88
  • 90. Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 89
  • 91. ANNIC Movie Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 90
  • 92. Example -­‐ Rules • Rule iden.fica.on in regula.ons; what one can 'argue' for and against. • Using previous modules. • Wyner and Peters (2011) Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 91
  • 93. Sample Outputs Consequence, list structure, and conjuncts of the antecedent. Excep.on, agent NP, deon.c concept, ac.ve main verb, theme. 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 92
  • 94. Sample Output Theme, deon.c modal, passive verb, agent with complex rela.ve clause. 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 93
  • 95. Sample Output -­‐ Overall 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 94
  • 96. Sample Output -­‐ XML 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 95 This is an inline representa.on, and not 'pure' XML as tags can overlap. There is also offset, which can be modified easily.
  • 97. Sample Output – ANNIC Search 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 96
  • 98. Gold Standards Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 97
  • 99. Teamware to Create Gold Standards 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 98
  • 100. Results of Annota.on • The annotators carry out their task and complete the project. • Carry out inter-­‐annotator agreement analysis. • Curate the disagreements to create a Gold Standard corpus. Can use this for machine learning. • Search the annota.ons using an online tool, e.g. ANNIC. 07/09/2014 Argumenta.on Summer School, Dundee A. Wyner, Univ of Aberdeen 99
  • 101. Addi.ons Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 100
  • 102. Add to Explorer (or Teamware) • Verbs for proposi.onal aZtudes, e.g. believe, know, hope and speech acts, e.g. stated, men7oned, guessed. • Opinion adverbials -­‐ obviously, so far as I know, scien7fically. • Ques.on words and markers – who, why, ? • Rhetorical connec.ves -­‐ elabora7on, example, contrast. • Others.... Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 101
  • 103. References Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen • Wyner, van Engers, Hunter (2010) • Wyner and Peters (2010, 2011) • Wyner, Schneider, Atkinson, and Bench-­‐Capon (2012) 102
  • 104. Thanks for your a[en.on! • Questions? • Contacts: – Adam Wyner adam@wyner.info Argumenta.on Summer School, Dundee 07/09/2014 A. Wyner, Univ of Aberdeen 103

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