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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Implicit Stereotypes: A Corpus-Based Study for Italian</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Wolfgang S. Schmeisser-Nieto</string-name>
          <email>wolfgang.schmeisser@ub.edu</email>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Giacomo Ricci</string-name>
          <email>giacomo.ricci@edu.unito.it</email>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Simona Frenda</string-name>
          <email>s.frenda@hw.ac.uk</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Mariona Taulé</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Cristina Bosco</string-name>
          <email>cristina.bosco@unito.it</email>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Interaction Lab, Heriot-Watt University</institution>
          ,
          <addr-line>The Avenue, Edinburgh, EH14 4AS, Scotland</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Universitat de Barcelona</institution>
          ,
          <addr-line>Gran Via de les Corts Catalanes, 585, Barcelona</addr-line>
          ,
          <country country="ES">Spain</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>University of Turin</institution>
          ,
          <addr-line>Dipartimento di Informatica, Corso Svizzera 185, 10149 Torino</addr-line>
          ,
          <country country="IT">Italy</country>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>aequa-tech</institution>
          ,
          <addr-line>Torino</addr-line>
          ,
          <country country="IT">Italy</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>Detecting stereotypes is a challenging task, particularly when they are not expressed explicitly. In this study, we applied an annotation schema from the literature designed to formalize implicit stereotypes. We analyzed implicit stereotypes about immigrants in two datasets: StereoHoax-IT and SterheoSchool, which are created from diferent sources. StereoHoaxIT consists of reactions on Twitter to specific hoaxes aimed at discriminating against immigrants, while SterheoSchool includes comments from teenagers on fake news generated in psychological experiments. We describe the annotation process, annotator disagreements, and provide both quantitative and qualitative analyses to shed light on how implicitness characterizes stereotypes in diferent texts. Our findings suggest that implicit stereotypes are often conveyed through logical linguistic relations, such as entailment and behavioral evaluations of immigrants.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;Implicit stereotype</kwd>
        <kwd>Corpora annotation</kwd>
        <kwd>Corpora analysis</kwd>
        <kwd>Italian language</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction and Background</title>
      <p>
        1Transl. "They throw away the food they are given only to go eat the
poor dogs. Where will we end up!"
2Transl. "Just as we respect them and the color of their skin, they, who
live in our countries, should show respect toward us."
phenomena, in particular those characterized by sub- the presence or absence of anti-migrant stereotypes, and,
jectivity, such as irony [23]. In this paper, we analyze if present, for other related categories such as whether
the implicit manifestation of stereotypes targeting immi- the stereotype was expressed implicitly or explicitly and
grants, using a well-defined annotation schema proposed which forms of discredit the stereotype could be
clasby Schmeisser-Nieto et al. [14] and tested on a subset sified at. This category is inspired by the Stereotype
of comments from Spanish newspapers (DETESTS [
        <xref ref-type="bibr" rid="ref9">5</xref>
        ]). Content Model (SCM) [
        <xref ref-type="bibr" rid="ref2">7</xref>
        ] and allowed us to observe the
This schema represents diferent criteria for determining stereotype from a perspective that encompasses
psycholthe implicitness of stereotypes in an attempt to formal- ogy and computational linguistics [26]. In section 3, we
ize the concept. Disentangling strategies of implicitness show how we extended this annotation to describe the
presents a significant challenge, often resulting in the dimension of implicitness6. StereoHoax-IT [27] is a
identification of multiple categories within the same text. contextualized multilingual dataset of tweets annotated
      </p>
      <p>
        Our main contributions consist of expanding the an- primarily for the presence of anti-migrant stereotypes.
notation with topics of stereotypes about immigrants [
        <xref ref-type="bibr" rid="ref9">5</xref>
        ] The dataset consists of replies to tweets identified as
conand the strategies to implicitness [14], as well as test- taining racial hoaxes specifically targeting migrants and
ing this schema on two existing Italian datasets. These collected from debunking websites from French, Italian
datasets share the same domain as those used for Spanish, and Spanish Twitter, collected from 2019 to 2021. Each
stereotypes about immigrants, and include data extracted message is provided with its “conversation head” (the
from Twitter (now X) as reactions to specific hoaxes message containing the source racial hoax), and its direct
(StereoHoax-IT) and comments written by high school parent message (if applicable). In this paper, we only use
students to two examples of fake news artificially cre- the Italian subset, which includes 3,123 instances. Due to
ated within psychological experiments (SterheoSchool) the rarity of the phenomenon, there is a significant class
as described in [24, 25]. Analyzing the annotated texts, imbalance: 472 instances (15%) contain a stereotype, 332
we noted that implicit stereotypes appear to be conveyed of which (70%) are implicit and 140 (30%) are explicit.
especially through logical linguistic relations like entail- SterheoSchool [28] consists of a selection of data
colment and the behavioral evaluation of immigrants in both lected in Italian schools during experiments conducted by
datasets. Moreover, in most cases, the annotators needed social psychologists [24, 25]. More precisely, it includes
to use contextual information to determine the presence the reactions of teenagers, who read two hoaxes
artifiof stereotypes. For example, in this case "Che centra lui e cially created and presented as news articles, recorded
Italiano!, può essere massacrato!" 3 (StereoHoax-IT) the au- via a cell phone interface. The hoaxes were designed to
thor of the message expresses a stereotype complaining elicit reactions to stereotypes in readers. For each news
that foreigners enjoy better treatment than Italians, who item, readers were asked to comment on the news and
can indeed be "macellati" (slaughtered). on the main character of the articles. These comments
      </p>
      <p>The rest of the paper is organized as follows: Sections 2 are also associated with metadata, such as the age and
and 3 describe the datasets and the annotation applied; declared gender of the author. By collecting data
generSections 4 and 5 present quantitative and qualitative anal- ated by teenagers, this corpus aims to fill a gap in the
yses of the annotated data; and Section 6 summarizes the literature in which teenagers are an underrepresented
results and provides guidance regarding future work. category in data annotated for text classification tasks.
We applied the annotation scheme mentioned above to
the news and comments. This corpus consists of 1,147
2. Datasets comments, of which 337 (33.8%) are annotated as
containing stereotypes, of which 152 (45%) are expressed in
an implicit form.</p>
      <sec id="sec-1-1">
        <title>In this work, we focus on two annotated corpora con</title>
        <p>
          taining implicit stereotypes developed within the
STERHEOTYPES project4 and the SterotypHate project5. Their
content is related to attitudes regarding immigrants and 3. Annotation
they share similar conversational structures and the same
annotation scheme. Each message in these datasets is The annotation scheme we applied on the two corpora
contextualized, i.e. collocated within a discourse thread is based on two diferent layers, topics of stereotypes and
or presented as a comment on a given news item. For implicitness strategies, as well as the need for context.
the annotation scheme, each message is annotated for The topics of stereotypes were firstly introduced
within an evaluation task, DETESTS [
          <xref ref-type="bibr" rid="ref9">5</xref>
          ], in which the
participants had to train models to decide whether a text
        </p>
        <sec id="sec-1-1-1">
          <title>3Transl. "That’s not the point, he is Italian! He can be slaughtered!"</title>
          <p>4STERHEOTYPES (Studying European Racial Hoaxes and
sterEOTYPES) is an international project funded by Compagnia di San
Paolo and VolksWagen Stiftung.
5StereotypHate is a project funded by Compagnia di San Paolo.
6The datasets will be made available for research purposes after the
acceptance of the paper in anonymized form.
contained stereotypes, and when they did, classify the
stereotype into ten diferent categories:
linguistic devices used to convey implicit stereotypes, we
have revised the criteria proposed in [14] as follows:
• Xenophobia victims Immigrants are perceived
as victims of xenophobia and discrimination.
They enrich culture and diversity and should have
the same rights as citizens.
• Sufering victims Immigrants are portrayed as
victims of poverty and violence in their places of
origin and as having to face dificult situations in
their host countries.
• Economic resources Immigrants are seen as an
economic resource. They do the jobs that locals
do not want to do, pay taxes and solve the
problems arising from low population growth.
• Migration control Immigrants present a threat
due to massive influxes and a lack of control at
the borders. Immigrants are illegal and should be
expelled. It is seen as an invasion.
• Culture and religion diferences Immigrants
suppose a loss of the in-group’s values and
traditions and the replacement of the target group’s
customs and religions. They are also seen as
uneducated and should adapt to their host country.
• Benefits Immigrants compete with the in-group
for resources such as public subsidies, school
places, jobs, health care and pensions. They are
privileged over the in-group.
• Public health Immigrants are thought to be
carriers of infections and diseases such as COVID-19,
Ebola and HIV.
• Security Immigration brings security issues. Due
to immigration, there is an increase in crime,
domestic violence, robbery, drug use, sexual assault,
murder, terrorist attacks and public disorders.
• Dehumanization Immigrants are seen as
inferior beings and are compared with animals,
parasites or scum. Their lives have less value than
those of the in-group.
• Other topics Any other immigration stereotypes
not covered in the previous categories.</p>
        </sec>
      </sec>
      <sec id="sec-1-2">
        <title>Context and implicitness strategies were initially pro</title>
        <p>posed as criteria that could help annotators to annotate
implicitness, since their vagueness may decrease
InterAnnotator Agreement (IAA) [14]. By context, we refer
to information contained in previous messages, which
is considered necessary to understand the meaning of
the message to be annotated, as in the following
example: "Sempre assolti...sempre misure e pesi diferenti". Context:
"Uccide anziana ebrea al grido di Allah Akbar. Assolto perché
drogato."7 (StereoHoax-IT). Regarding the strategies and</p>
        <sec id="sec-1-2-1">
          <title>7Transl. "Always acquitted...always diferent measures and weights."</title>
          <p>Context: "Kills elderly Jewish woman while shouting ‘Allah Akbar.’
Acquitted because he was on drugs."
• World knowledge World knowledge refers to
the shared cultural, social and historical
knowledge needed to interpret messages, e.g., "La scuola
si inchina all’islam: l’aceto è bandito dalle mense." 8
(StereoHoax-IT)
• Figures of speech Every figure of speech
except for irony and sarcasm, and humor and jokes.</p>
          <p>For instance, metaphor, rhetorical questions,
euphemisms or reported speech, e.g., "Chi è quel
pazzo che si mette in casa uno di questi? Un suicidio" 9
(StereoHoax-IT)
• Irony/Sarcasm The message expresses a
meaning that is the opposite of what is said, e.g. in "Che
bella gente fanno arrivare.....che bello avere un paese
pieno di risorse pronte a tutto.....ma proprio a tutto." 10
(StereoHoax-IT)
• Humor/Jokes Jokes about a target group
often use stereotypes and may or may not include
irony, e.g. in "Chissà se ha detto:"Cibo no buono"." 11
(StereoHoax-IT)
• Extrapolation The target refers to an individual
or specific members of a social group, not the
group as a whole, e.g. in "Classico del sud-italia</p>
          <p>Maleducata" 12 (SterheoSchool)
• Imperative/Exhortative Calls to take certain
actions related to the target group, e.g. "Come in</p>
          <p>Cina FUCILATELO" 13 (StereoHoax-IT)
• Entailment/Evaluation Logical relation
between two sentences in which the condition of
truth of sentence A implies the truth of sentence
B. The implicit stereotype is implied in sentence
A. An evaluation of the author’s or in-group’s
thoughts, emotions and behaviors, rather than
content about the out-group or target group,
can be considered as a type of entailment, e.g.
"Saranno fuori o liberi presto" 14(StereoHoax-IT) is
the answer to a racial hoax in which a group of
immigrants rape and murder a teenage girl. With the
author’s evaluation of the situation, it is entailed
that immigrants are immune from punishment.
• Other implicitness Other types of implicitness
not considered in the previous categories.
e.g. "al giorno d’oggi non ci si può fidare di nessuno
una persona ripugnante" 15(SterheoSchool)
8Transl. "The school bows to Islam: vinegar is banned from canteens."
9Transl. "Who’s that fool who takes one of these into his house? a
suicide"
10Transl. "Such nice people they bring in... how nice it is to have a</p>
          <p>country full of resources ready for anything... anything at all"
11Transl. "I wonder if he said: «Food no good»"
12Transl. "Typical of Southern Italy"
13Transl. "SHOOT HIM like in China"
14Transl. "They will be out or free soon"
15Transl. "nowadays you can’t trust anyone a repulsive person"
Table 1 stereotypical topics that portray immigrants as threats,
Inter-annotator agreement test using Fleiss’ kappa ( ) coefi- the security issue is highly prevalent in both datasets.
cient on the categories of implicitness and stereotype topics A common trend shows that the most frequent
implicof the StereoHoax-IT and the SterheoSchool corpora. itness strategy in both datasets is ‘entailment/evaluation’,
Label StereoHoax-IT SterheoSchool accounting for 64% in StereoHoax-IT and 80% in
SterheoSchool. To a lesser degree, ‘extrapolation’ appears in
SXuenferoipnhgovbiciativmicstims 0.04.957 0.05.050 both datasets, with 13% in the former and 19% in the
latEconomic resource 0.48 0.50 ter, respectively. Other represented strategies that exceed
Migration control 0.77 0.55 10% of instances are only found in StereoHoax-IT.
Culture &amp; religion 0.75 0.71 The label ‘context’ has a high prevalence in both
Benefits 0.75 0.62 datasets, accounting for 38% in StereoHoax-IT and 80%
SPeucbulircithyealth 00..8816 00..5604 in SterheoSchool. This is expected, as it depends on the
Dehumanization 0.71 0.71 methodology to produce the comments—spontaneous
Other topics 0.52 0.43 versus controlled—and the variety of contexts: two
fake news for StereoSchool and 50 racial hoaxes for
Context 0.72 0.50 StereoHoax-IT. The limited amount of data unfortunately
World knowledge 0.52 0.51 does not allow us to reliably evaluate a correlation
beFigures of speech 0.68 0.70 tween ‘context’ and certain implicitness strategies, as
Irony/Sarcasm 0.70 0.50 shown in Table 3, except for the association between
‘enHumor/Jokes 0.52 No cases tailment/evaluation’ and ‘context’ across both datasets.
Extrapolation 0.51 0.53 The correlation between ‘implicitness’ and ‘context’ is
IEmntpaeirlmateivnet//EExvhaoluratatitoivne 00..7435 00..4593 also shown in Bourgeade et al. [27], with significant
assoOther implicitness 0.51 0.52 ciations of the aforementioned labels in three languages:
French, Italian and Spanish. In StereoHoax-IT, the
correlations between the ‘context’ and ‘irony/sarcasm’,
‘extrap</p>
          <p>The annotation was carried out on the Label Studio olation’ and ‘imperative/exhortative’ are also significant,
platform by three native Italian speakers with a back- whereas the category of other implicitness strategies is
ground in linguistics, some of whom specialized in NLP. also significantly correlated in SterheoSchool, which can
They achieved an acceptable to good IAA in the majority be analyzed qualitatively to determine if there is a pattern
of cases, as reported in Table 1, which varies across cate- among them. The other strategies do not have
represengories and corpora. By observing Table 2, we can see that tative instances that allow for analyzing them
comparaonly a few topics have been marked by the majority of tively, except for ‘extrapolation’, which is significantly
annotators , while not all the implicit criteria have been correlated in StereoHoax-IT but not in SterheoSchool.
identified in the texts (i.e., ‘humor/jokes’). In terms of co-occurrences between topics and implicit
4. Quantitative Analysis strategies, we can observe from Table 4 that there is also
a great disparity in both datasets. Focusing on the two
Table 2 shows the distribution of the disaggregated anno- topics with the highest representation in SterheoSchool
tations across both datasets. Columns 0%, 33%, 67% and (Culture &amp; religion, 51%, and security, 35%), which
ac100%, respectively, indicate the number of instances per count for the majority of the corpus, we can analyze
label that were annotated by no annotator (0%), by one some diferences with StereoHoax-IT. Firstly, ‘culture &amp;
annotator (33%), by two annotators (67%) and by all three religion’ is expressed primarily through entailments or
annotators (100%). Column % positive class shows the per- evaluations (65 co-occurrences) and secondarily through
centage of the label voted by the majority of annotators, extrapolations in SterheoSchool. In contrast, the
distriand its total number of cases in parentheses. bution of strategies used to represent ‘culture &amp; religion’</p>
          <p>Firstly, an inconsistency in the distribution of labels stereotypes is more evenly spread in StereoHoax-IT. A
can be observed since SterheoSchool has a representation similar pattern is observed with the topic of ’security’,
of labels of more than 10% on only four labels. This dispar- which, while concentrating strategies in
’entailment/eity is due to the extraction methods of each dataset: the valuation,’ also utilizes a range of other strategies,
partictopics of the racial hoaxes used to extract the dataset were ularly ‘extrapolation’ and ‘imperative/exhortative’. With
more balanced in StereoHoax-IT than in SterheoSchool, these co-occurrences, we can reafirm that the diferent
with the latter focusing generally on security and cultural methods to extract the data have an impact on the
characdiferences that are discussed in the two only contexts teristics of it, and therefore, its distribution of labels. For
provided to the students for their comments. However, instance, the messages were written in a non-controlled
while in the former there is a representation of all the environment, which gives the authors the freedom to
express themselves without constrains. Moreover, the
Labels
Xenophobia victims
Sufering victims
Economic resource
Migration control
Culture &amp; religion
Benefits
Public health
Security
Dehumanization
Other topics
Context
World knowledge
Figures of speech
Irony/Sarcasm
Humor/Jokes
Extrapolation
Entailment/Evaluation
Imperative/Exhortative
Other implicitness
topics in StereoHoax-IT are more balanced, as seen in
the distribution of ‘entailment/evaluation’, which is also
used in ‘migration control’, ‘benefits’, ‘public health’ and
‘dehumanization’. On the other hand, in SterheoSchool,
both initial fake news have the same narrative features,
such as describing an aggression and highlighting the
origin of the aggressor, thus eliciting a reaction in the
readers related to these topics. The example "Siamo alla
follia: ad Agrigento autobus gratis agli immigrati per evitare
violenze e aggressioni." 16 (StereoHoax-IT) is related to security
expressed through extrapolation. The example "Un
cristiano che entrasse in una moschea in un paese arabo e sputasse
per terra sopravviverebbe pochi secondi." 17 (StereoHoax-IT)
highlights cultural and religious diferences by the
evaluation of a hypothetical situation.
16Transl. "It’s crazy: in Agrigento, free buses for immigrants to prevent</p>
          <p>violence and aggressions."
17Transl. "A Christian entering a Mosque in an Arab country and
spitting on the ground would survive a few seconds."</p>
        </sec>
      </sec>
    </sec>
    <sec id="sec-2">
      <title>5. Qualitative analysis</title>
      <sec id="sec-2-1">
        <title>To deepen the analysis of implicitness strategies and their interaction with diferent topics, we explore some messages to uncover the linguistic structures that are characteristic of implicit communication.</title>
        <p>Example 1 has been annotated with the topic ‘public
health’ and ‘figures of speech’ and ‘Irony/Sarcasm’ for
the strategy of implicitness; all labels achieved a 67% IAA.</p>
        <p>1) Governo di involtini primavera!!! 18 (StereoHoax-IT)
In the context given for this message, the author
complains that the government did not use more
restrictive measures against Chinese children during the early
stages of COVID-19. First, an ironic reading, i.e., as
stating A to mean not-A, is triggered by the metonymy
“spring rolls” [29], identifying Chinese citizens through
a traditional Chinese dish. Second, disapproval is
conveyed showing a kind of favorable attitude of the Italian
18Trasl."Spring rolls government."
government toward Chinese children. also interesting, and has been studied especially in social</p>
        <p>Example 2 was annotated as ‘culture &amp; religion’ by all media [32, 33], as a means to lower the negative social
three annotators. In terms of the implicitness strategies, cost of what has been said. The two categories that most
it was labeled as both ‘extrapolation’ and ‘entailment/e- frequently co-occur with ‘irony/sarcasm’ in
StereoHoaxvaluation’ by two out of the three annotators. IT are ‘figures of speech’ (out of 35 instances, six are also
2) Venezia, donne velate sputano al crocifisso. 19 ironic) and ‘humor/jokes’ (out of three cases, two are
(StereoHoax-IT) ironic), as in the next example:
In this case, the noun phrase “veiled women” is a case of 5) @Belle facce intelligenti! Viva Lombroso!22 (67%
Hulexical narrowing, i.e., a lexical item conveys a meaning mor/Jokes, 67% Irony/Sarcasm, StereoHoax-IT)
that is more specific than the item’s encoded meaning. We found messages in which ‘entailment/evaluation’
coThe reader selects a more specific meaning on the basis occurs with ‘irony/sarcasm’, but this correlation should
of stereotypes and world knowledge [30] of the mean- be analyzed in depth to be considered relevant, as 64% of
ing of “veiled women”, which denotes a set of women instances were annotated as ‘entailment/evaluation.’
who wear a veil, narrowed to mean Muslim women. This
equalization arises from the stereotype that posits that 6. Conclusions
if a woman wears a veil, she is a Muslim. Furthermore,
the absence of the determiner in the noun phrase, that In this paper, we applied an annotation scheme for
analyzusually indicates a generic reference, combined with the ing the implicitness of stereotypes against immigrants
acimperfective aspect and present tense of the verb, may cording to two main dimensions (i.e., topics and strategies
suggest a habitual interpretation of the predicate "spit on for making the content implicit) to the Italian
StereoHoaxthe crucifix" [ 31]. ‘Extrapolation’ strategy here refers to IT and SterheoSchool corpora. Adding these two layers
the attribution of this action to the entire category. of annotation allowed us to observe that annotators need</p>
        <p>Among the more frequently agreed implicitness strate- to use contextual information to determine the presence
gies, there are ‘imperative/exhortative’ and ‘figures of of stereotypes especially, when specific strategies have
speech’, which have linguistic and punctuation features been used by the author of the message (irony/sarcasm,
closer to explicitness: the former is associated with a spe- extrapolation, entailment/evaluation, and
imperative/excific grammatical mood and the exclamation mark, while hortative). Moreover, implicit stereotypes appear to be
the latter is associated with a question mark (considering conveyed mainly through logical linguistic relations such
that rhetorical questions are frequently annotated as a as the entailment and behavioral evaluation of
immiifgure of speech), see e.g.: grants and, in fewer cases, via ‘imperative/exhortative’,
3) Se non fate niente Fra 10 anni l’italia sarà tutta musul- ‘irony/sarcasm’ and ‘extrapolation.’
mana!20 (StereoHoax-IT) As future work, we plan to perform a comparative
4) Come ci si può sentir sicuri in una società che permette analysis with the datasets in Spanish, which have already
questo? meschina21 (SterheoSchool) been annotated with this schema, in order to understand
The high IAA for the category of ‘irony/sarcasm’ is cultural analogies and diferences in portraying
immigrants as threats, enemies or victims.
19Trasl."Venice, veiled women spit on the crucifix."
20Trasl."If you do nothing In 10 years Italy will be completely Muslim"
21Trasl."How can one feel secure in a society that allows this? mean"
22Trasl."Nice smart faces! Long life Lombroso!"</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Acknowledgments</title>
      <sec id="sec-3-1">
        <title>The work of Wolfgang Schmeisser-Nieto is funded by</title>
        <p>the project StereotypHate (Compagnia di San Paolo for
the call ‘Progetti di Ateneo - Compagnia di San Paolo
2019/2021 - Mission 1.1 - Finanziamento ex-post’).</p>
        <p>The work of Cristina Bosco is partially funded by the
same project.
for Italian. Final Workshop (EVALITA 2020), vol- https://aclanthology.org/E17-1025.
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