Arguments in Parliamentary Negotiation: A Study of Verbatim
Records
Mare Koit
a
Institute of Computer Science, University of Tartu, Narva mnt 18, Tartu, Estonia
Keywords: Argument, Negotiation, Parliament, Verbatim Record, Knowledge Representation, Annotated Corpus.
Abstract: Verbatim records of sittings of the Estonian Parliament are studied in this paper. The general structure of the
discussions is presented. Arguments used in negotiation are considered as consisting of premises and claims.
The relations between the arguments (attack, rebuttal, support) are determined with the aim to create a corpus
where arguments are annotated. Our further aim is the automatic recognition of arguments and their relations
in Estonian political texts. To our knowledge, this is the first attempt towards modelling Estonian political
argumentation.
1 INTRODUCTION
Parliamentary discourse is an important resource
because it contains impactful information and special,
formalised and often persuasive and emotional
language. The empirical study of parliamentary
discourse contributes to an understanding of how
policy issues are framed. The study can also be related
to comparative assessments of the deliberative
performance of different parliaments (Bara et al. 2007).
There are many ongoing initiatives for compiling
digital collections of parliament data (Working 2017).
The recent CLARIN-PLUS survey on parliament data
has identified over 20 corpora of parliamentary
records, with over half of them being available within
the CLARIN infrastructure (Fišer, Lenardič 2018).
The data can be used for linguistic, historical,
political, sociological etc. research.
Parliamentary debates are full of arguments.
Analysing argumentation from a computational
linguistics point of view has recently led to a new eld
called argumentation mining. The review of Atkinson
et al. (2015) considers the development of articial
tools that capture the human ability to argue. Such
systems can be used when modelling political
argumentation since they are able to extract
arguments and relations between them automatically.
In the current paper, we study negotiations on
motions in the Estonian Parliament (Riigikogu) based
a
https://orcid.org/0000-0002-7318-087X
on verbatim records of the sittings (in Estonian). In
the records, repetitions and disuencies are omitted,
while supplementary information such as speaker
names are added. In the paper, we are looking for
arguments presented in negotiations for and against a
motion. To our knowledge, this is the first attempt to
analyse and model the formal structure and relations
of arguments in Estonian political discourse.
The paper is structured as follows. Section 2
describes related work. In Section 3, we examine one
randomly selected discussion in Riigikogu by using
verbatim records of the sittings. We consider the
arguments presented by the members of the parliament
and determine the inter-argument relations. Section 4
discusses some problems of annotating the arguments
with the aim to create a corpus in order to prepare
automatic recognition of arguments. Section 5 draws
conclusions and figures out the future work.
2 RELATED WORK
A lot of work has been done when studying political
discourse.
Bara et al. (2007) examine one UK parliamentary
debate on abortion with the aim to identify the
prominent themes in debate and to assess how far
speakers who favour different positions adopt a
distinct pattern of discourse.
822
Koit, M.
Arguments in Parliamentary Negotiation: A Study of Verbatim Records.
DOI: 10.5220/0009128908220828
In Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) - Volume 2, pages 822-828
ISBN: 978-989-758-395-7; ISSN: 2184-433X
Copyright
c
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
Vilares and He (2017) propose a Bayesian
modelling approach where topics are modelled as
latent variables. The model is evaluated on debates
from the House of Commons of the UK Parliament.
This is the rst novel work towards topic modelling.
Addawood et al. (2017) investigate the question
of whether opinion mining techniques can be used on
Congressional debates or not.
Venkata et al. (2018) provide a dataset for the
synopsis of Indian parliamentary debates and perform
stance classification of speeches, identifying if the
speaker is supporting the bill. Based on manual
analysis of the debates, they develop an annotation
scheme of four mutually exclusive categories to
analyse the purpose of the speeches.
Special attention has been paid to argumentation
in political discussions.
Walker et al. (2012) analyse deliberations and
debates by using the Internet Argument Corpus. The
corpus includes the posts from a website for political
debate where the debates are annotated for
argumentative markers like degrees of agreement
with previous post, cordiality, audience direction,
combativeness, assertiveness, emotionality of
argumentation, and sarcasm.
In parliamentary discourse, politicians expound
their beliefs and ideas through argumentation, and to
persuade the audience, they highlight some aspect of
an issue, which is commonly known as framing.
Naderi and Hirst (2015) examine how to identify
framing strategies in argumentative political speech.
They use a corpus of speeches from the Canadian
Parliament, and examine the statements with respect
to the position of the speaker towards the discussed
topic (Pro, Con, or No stance).
Petukhova et al. (2015) use the Information State
Update (ISU) approach to model the arguments of the
debaters and the support/attack links between them as
part of the formal representations of a participant’s
information state. They consider the identication of
claims and evidence relations to their premises as an
argument mining task. The ISU model provides
procedures for incorporating beliefs and expectations
shared between speaker and hearers in the tracking
model.
Lippi and Torroni (2016a) investigate how to
improve claim detection for argument mining, by
employing features from text and speech in
combination. They develop a machine learning
classier and train it on an original dataset based on
the 2015 UK political elections debate.
Petukhova et al. (2017) have collected the
Metalogue Debate Corpus that includes 400
arguments from six different bilingual
(English/Greek) speakers. The corpus is used to
design a Virtual Debate Coach, in order to train young
parliamentarians on how to debate successfully.
Although it is often difcult to dene clear properties
of persuasive debate, there are certain linguistic,
prosodic and body language features that correlate
with human judgments of such behaviour.
Haddadan et al. (2018) present annotation
guidelines for annotating arguments (their premises
and claims) in political debates. The dataset is taken
from the Commission on Presidential Debates
website which is an independent non-prot
corporation sponsoring U.S. presidential and vice-
presidential debates.
Menini et al. (2018) apply argumentation mining
techniques, in particular relation prediction, to study
political speeches – monologues, where there is no
direct interaction between opponents. They have
created a corpus, based on the transcription of
speeches and ofcial declarations issued by Nixon
and Kennedy during 1960 Presidential campaign, of
argument pairs annotated with the support and attack
relations. They use a tool called OVA+ (Janier et al.
2014), an on-line interface for the manual analysis of
natural language arguments.
Many other studies have contributed to
development of formalisms and tools for analysing
arguments.
Chesňevar et al. (2006) introduce a specication
for an argument interchange format intended for
representation and exchange of data between various
argumentation tools and agent-based applications.
Reed et al. (2008) describe a written corpus of
argumentative reasoning. Arguments have been
analysed using techniques from argumentation theory
and have been marked up. The authors present
experiences with initial pilot data collection, which
raised a number of key questions that frame
challenges for argument corpora in general.
Besnard and Hunter (2014) consider a deductive
argument as a pair where the rst item is a set of
premises, the second item is a claim, and the premises
entail the claim. This can be formalised by assuming
a logical language for the premises and the claim, and
logical entailment (or consequence relation) for
showing that the claim follows from the premises.
Stab and Gurevych (2014) present a novel
approach to model arguments, their components and
relations in persuasive essays in English. The
annotation scheme includes the annotation of claims
and premises as well as support and attack relations
for capturing the structure of argumentative
Arguments in Parliamentary Negotiation: A Study of Verbatim Records
823
discourse. The authors conduct a manual annotation
study with three annotators on 90 persuasive essays.
Amgoud et al. (2015) consider an argument as
reasons in favour of a claim. It is made of three parts:
a set of premises representing the reasons, a
conclusion representing the supported claim, and a
connection showing how the premises lead to the
conclusion. They propose a language for representing
such arguments that captures the various forms of
arguments encountered in natural language, and
demonstrate that it is possible to represent attack and
support relations between arguments as formulas of
the same language.
MARGOT (Mining ARGuments frOm Text) is a
web server for the automatic extraction of arguments
from text (Lippi, Torroni 2016b). It focuses on
detection of argument components (claim and
evidence). A claim is a general, typically concise
statement that directly supports or contests a topic
under debate, whereas evidence is a text segment that
directly supports a claim. The tool currently supports
only English.
Atkinson et al. (2017) summarise that recent
developments are leading to technology for articial
argumentation, in the legal, medical, and e-
government domains, and interesting tools for
argument mining, for debating technologies, and for
argumentation solvers are emerging. The extracted
arguments will represent the nodes in an argument
graph and the links are the relations between the
arguments.
3 ARGUMENTS PRESENTED BY
THE MEMBERS OF
RIIGIKOGU
In this paper, we are analysing the verbatim records
of discussions held in the Parliament of Estonia, in
order to figure out the structure of the arguments
presented in negotiation. Our current aim is to create
a corpus where arguments are annotated. Such a
corpus will contribute to the automatic recognition of
arguments and can thereby promote studies on
Estonian political discourse.
3.1 Empirical Material
Our empirical material is formed by the records of the
Parliament of Estonia – Riigikogu (cf. Riigikogu). An
important task of the Riigikogu is the passing of acts
and resolutions. Acts are the result of work in
multiple stages. The first stage of legislation involves
the drafting of a bill (a draft act). During the second
stage, the bill is initiated in the Riigikogu. The bill
will then pass three readings (in exceptional cases
two), during which it is refined and amended. The
proceeding of a bill is managed by the relevant
leading committee. After having been passed by the
Riigikogu, the act is sent to the President of the
Republic for proclamation, and is then published in
State Gazette. The general structure of the process in
Riigikogu is presented in Fig. 1 (cf. Koit et al. 2019).
The authors of turns are given in italics.
- - 1
st
reading
- - initiator – Government
Presenter (Minister): Report
{
MP: Question
Presenter: Giving information
}
Co-presenter (a member of leading committee): Report
{
MP: Question
Co-presenter: Giving information
}
- - negotiation
{
MP: argument
}
- - 2
nd
reading
Presenter (a member of leading committee): Report
on amendment motions
{
MP: Question
Presenter: Giving information
}
- - negotiation
{
MP: argument
}
- - voting on amendment motions
- - 3
rd
reading
- - negotiation
{
MP: argument
}
- - final voting
Figure 1: The general structure of discussions in Riigikogu.
The winding brackets ‘{‘ and ‘}’ connect a part that can be
repeated; ‘- -’ starts a comment; MP– any member of
Riigikogu. The authors of turns are given in italics.
Verbatim records of sittings of the Riigikogu (in
Estonian) are accessible on the web as pdf files. For
the current study, we have randomly chosen a draft
act on social care that was proceeded in 2018 (the
records of three sittings include 14,662 running words
in total). The aim of the act is to create an additional
supporting system for youth security in order to
decrease the rate of the unemployment of young
ICAART 2020 - 12th International Conference on Agents and Artificial Intelligence
824
people (16–26 years) which is twice the average
unemployment (14.1% vs 6%). The debate ends after
voting with adopting of the act by the members of
Riigikogu (MPs).
3.2 Arguments
An argument is a series of statements (in a natural
language), called the premises, intended to determine
the degree of truth of another statement – the claim.
Therefore, an argument consists of two parts: of one
or more premises and of a claim. These parts can be
presented in one or more sentences. There are three
types of relations between the arguments: attack,
support, and rebuttal (Amgoud et al. 2015).
When analysing persuading essays, Stab and
Gurevych (2014) make a distinction between the
major claim and a claim. In parliamentary
discussions, we similarly can differentiate the major
claim and a claim of an arbitrary argument. The major
claim together with its premises is given in the report
of Minister and it is always ‘to accept the bill’ (Fig.1).
As a rule, the claim of a supporting argument
presented in following negotiation, coincides with the
major claim. The claim of a rebutting argument is
opposite: do not accept the bill. The claim of an
attacking argument depends on a previous argument
that is under attack. The arguments and relations will
be illustrated by the following examples.
When taking the floor in negotiation, the members
of Riigikogu are always presenting their arguments in
more than one sentence. A premise and a claim are
located in different sentences. In some cases, the
claim is missing (is default), mostly when it coincides
with the major claim or, on the contrary, when it is
opposite. Typically, the arguments have more than
one premise.
In the analysed negotiations, premises and claims
of arguments were manually annotated by the author
of the paper, following (Stab, Gurevich 2014) and
(Amgoud et al. 2015). (In consequence, the
annotation is rather subjective.) Let us give some
examples of arguments and relations between them.
Major claim (‘to accept the bill’) and its premises
are given at the beginning of the first reading, in the
reports of Minister and the member of a leading
committee (Fig. 1). Example 1 presents some of the
premises given by Minister.
Example 1. Three premises of the major claim
presented by Minister.
(1)
<premise>
Teatavasti on Eestis noorte töötuse määr ligi kaks korda
suurem kui keskmine töötuse määr ning viimasel ajal on see
vaatamata üldisele heale tööturu seisule hoopis suurenema
hakanud.
As known, the unemployment of young people is
twice the average unemployment and it is increasing
although the general situation on the work market is
good.
</premise>
(2)
<premise>
Noortegarantii tugisüsteemi eesmärk ongi vähendada
mittetöötavate ja mitteõppivate noorte arvu.
The aim of the supporting system is to decrease
the number of the young people who are neither
working nor learning.
</premise>
(3)
<premise>
Kuna tegemist on andmetöötlusega, siis on selle
süsteemi kasutamiseks vaja seaduslikku alust.
The legislative basis is needed because there is
data processing.
</premise>
The following counterarguments presented by
MPs in negotiations include different claims:
negation of the major claim (Example 2) and
derivatives of the major claim (Examples 3 and 4
where premises of the major claim are attacked).
Example 2. Argument rebutting the major claim.
<argument
K
>
- - rebutting
<premise>
Eelnõu kohaselt võimaldatakse omavalitsustel
proaktiivselt pakkuda potentsiaalselt abi vajavatele noortele
inimestele tuge kas tööelu alustamiseks või haridusellu
naasmiseks.
The purpose of the bill is to provide proactive help
by a local government to young people who need
support for starting to work or for returning to
education.
</premise>
/---/
<premise>
Kuid kes oleks osanud arvata, et selle hea eesmärgi
saavutamiseks minnakse nii kaugele, et hakatakse isikuandmeid
töötlema liiga massiliselt ehk hakatakse tegelema omaalgatusliku
nuhkimisega.
But who could believe that in order to achieve this
nice goal, personal data will be processed so
massively, i.e. people will be tracked down.
</premise>
Arguments in Parliamentary Negotiation: A Study of Verbatim Records
825
<claim>
Sellist seadust meile tegelikult vaja ei ole.
We don’t need such a law.
Kehtivas hoolekandeseaduses on olemas kõik hoovad
statistiliste andmete kogumiseks ja analüüsimiseks ning noorte
inimeste abistamiseks.
The valid law already includes all the instruments
necessary for collecting and analysing statistical
data.
</claim>
</argument
K
>
The argument in Example 2 strongly rebuts the
major claim (s. Amgoud et al. 2015).
Example 3. Argument attacking a reason of the
major claim.
<argument
L
>
- - attacking
<premise>
Meie ees olev eelnõu on kõige ilmekam näide õigusnormide
loomise kohta seal, kus neid tegelikult vaja ei ole.
This bill is a clear example of creating
unnecessary juridical norms.
</premise>
/---/
<claim>
Seega oleme seisukohal, et abi vajavaid noori on vaja aidata,
kuid inimene peab ise abi saamiseks pöörduma või keegi hädas
olemisest märku andma.
Therefore, our standpoint is that a young man
who needs an assistance will be assisted but he has to
appeal himself or anybody else has to give a signal
about his difficulties.
</claim>
</argument
L
>
The argument in Example 3 weakly attacks the
reason of a supporting argument presented in the
Minister’s report.
Example 4. Argument attacking a reason of the
major claim.
<argument
M
>
- - attacking
/---/
<premise>
Ei ole ka piisavalt argumenteeritud ega suudetud selgitada,
miks on vaja sellisel määral noorte eraellu sekkuda.
It is not enough argued, why it is necessary to
intervene into private life of young people in such a
degree.
</premise>
/---/
<claim>
/---/
Me vaidlustame valitud meetodit ja selle ulatust.
We protest the method and its extent.
</claim>
</argument
M
>
The argument in Example 4 similarly to Example
3 weakly attacks the reason of the argument presented
by Minister in his report.
The following Examples (5 and 6) are the
supporting arguments. Both of them are presented as
reactions to previous attacking arguments.
Example 5. A supporting argument.
<argument
N
>
- - supporting
<claim>
Sotsiaaldemokraatlik Erakond kindlasti toetab seda eelnõu.
Social democrats definitely support this bill.
</claim>
<premise>
Selleks, et seda pilootprojekti läbi viia ja et oleks tagatud
andmekaitse, on vaja see seaduses sätestada.
In order to perform this pilot project and to
guarantee the data protection, it is necessary to
legalise it.
</premise>
<premise>
Me teame ju väga täpselt, et meie riigis on kogu aeg iga
inimene tähtis.
We precisely know that every person in our
country is important every time.
</premise>
<premise>
Samas me teame, et paljud noored, kes on oma koolitee pooleli
jätnud, kes hooldavad kodus oma vanemaid või kellel on mingi
muu põhjus, on jäänud kõrvale meie ühiskonna rutiinist,
tavapärasest arengust.
We also know that many young people who have
interrupted their education are maintaining their
parents at home or they have another reason to hang
back from our society, our usual development.
</premise>
/---/
</argument
N
>
The claim of the argument in Example 5 is
presented before its premises and it coincides with the
major claim. The argument supports the major claim.
Example 6. A supporting argument.
<argument
P
>
- - supporting
<premise>
Selle seadusemuudatuseta võib osa noori jääda aktiivsest
ühiskonnaelust kõrvale, ehkki teenused ja võimalused nende
aitamiseks on olemas.
Without this amendment, some of the young
people will be eliminated from active life although we
have all the means to help them.
ICAART 2020 - 12th International Conference on Agents and Artificial Intelligence
826
</premise>
/---/
<premise>
Olgu veel kord üle kinnitatud, et mingiks nuhkimiseks ei lähe
– kõik toimingud saavad olema kooskõlas andmekaitse reeglitega.
It should be stressed once more that no pursuing
will be carried out – all the actions will be done
according to rules of data protection.
</premise>
<claim>
(major claim)
</claim>
</argument
P
>
The major claim is not explicitly presented in the
argument. However, it by default coincides with the
major claim. Therefore, the argument supports the
major claim.
4 DISCUSSION
The paper makes the first attempt to annotate and
analyse the arguments in Estonian political discourse.
The empirical material is formed by the verbatim
records of sittings held in the Estonian Parliament. As
a case study, proceeding of the draft act on social care
is considered. Arguments and different relations
between them (attack, support, and rebuttal) are
annotated. In the analysed records, arguments that
support the motion are prevailing over the
counterarguments and the act is approved by the
Parliament.
Every argument consists of two parts – one or
more premises and a claim. In parliamentary
discussions, the presented arguments typically
include more than one premise and they consist of
many sentences. The claims can be explicit or implicit,
by default derived from the premises. In some cases,
MPs in their turns also make proposals/amendments
in addition to rebutting or attacking arguments. The
situation is different as compared with persuasive
essays where premise(s) and a claim are typically
located in the same sentence (Stab, Gurevich 2014).
The inner structure of arguments presented in
parliamentary negotiations needs additional study.
Some tools can be used for (manual) annotation of the
arguments as well as visualising the attack and
support relations between them (e.g. Janier et al.
2014). A challenging further research question is a
comparative study of political argumentation in
Estonian parliament, on one hand, and in other
parliaments, in different political cultures and
different languages, on another hand.
5 CONCLUSIONS
Verbatim records of sittings of the Parliament of
Estonia can be accessed online. For the current study,
an act on social care is chosen as an example. The
draft act passed three readings. The arguments
presented in the process of adopting the act are
annotated. The structure of arguments and the
relations between the arguments are analysed. Some
examples of the arguments are given.
This study is the first step towards automatic
analysis of political arguments in Estonian
parliamentary discussions. The current task is the
development of the annotation scheme and creating a
corpus where arguments are annotated. The automatic
recognition of arguments in Estonian parliamentary
discourse and comparison with other parliaments
remains for the further work.
ACKNOWLEDGEMENTS
This work was supported by institutional research
funding IUT (20-56) of the Estonian Ministry of
Education and Research, by the European Union
through the European Regional Development Fund
(Centre of Excellence in Estonian Studies), and by the
Estonian Research Council grant no. 1226. The
author is also very thankful to anonymous reviewers
for their valuable comments.
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