alemiaschi/clic-it_corpus huggingface dataset:
Gamification for IR: The Query Aspects Game
Authors: Giorgio Maria Di Nunzio, Maria Maistro, Daniel Zilio (Università di Padova, 2016)
Topic: Chatbots and Dialogue Systems

Abstract
The creation of a labelled dataset for IR purposes is a costly process. For this reason, a mix of crowdsourcing and active learning approaches have been proposed in the literature in order to assess the relevance of documents of a collection given a particular query at an affordable cost. In this paper, we present the design of the gamification of this interactive process that draws inspiration from recent works in the area of gamification for IR. In particular, we focus on three main points: i) we want to create a set of relevance judgements with the least effort by human assessors, ii) we use interactive search interfaces that use game mechanics, iii) we use NLP to collect different aspects of a query. }

Introduction
In IR, the performance of a system is evaluated using experimental test collections. These collections consist of a set of documents, a set of queries, and a set of relevance judgments, where each judgement explains whether a document is relevant or not to each query. The creation of relevance judgements is a costly, time-consuming, and non-trivial task; for these reasons, the interest in approaches that generate relevance judgements with the least amount of effort has increased in IR and related areas (i.e., supervised ML algorithms). In the last years, mixed approaches that use crowdsourcing AUTHOR and active learning AUTHOR have shown that it is possible to create annotated datasets at affordable costs. Specifically, crowdsourcing has been part of the IR toolbox as a cheap and fast mechanism to obtain labels for system evaluation. However, successful deployment of crowdsourcing at scale involves the adjustment of many variables, a very important one being the number of assessors needed per task, as explained in AUTHOR.

Conclusion
In this work, we presented the requirements of the design of an interactive interface that uses game mechanics together with NLP techniques to generate variation of an information need in order to label a collection of documents. Starting from the successful experience of the gamification of a machine learning problem AUTHOR, we are preparing a new pilot study of the `query aspects game' that will be used to generate relevant documents for two TREC tracks: the Total Recall track and the Dynamic Domain track. The results of this study will be available at the end of November 2016, and can be presented and discussed at the workshop.
Sequenze N+pN (nome comune + nome proprio): descrizione linguistica da un corpus dell’italiano.
Authors: Felicia Logozzo (Università di Roma Tor Vergata, 2016)
Topic: Lexical and Semantic Resources and Analysis

Abstract
The contribution describes the most significant N+pN structures extracted from the corpus of La Repubblica 2002-2005.

Introduction
The data covered by the analysis were derived from the corpus of La Repubblica 2002-2005 (about 20 million tokens), by means of T2K1 (Text to Knowledge), an automatic system for the extraction and organization of knowledge from texts. The software was asked to select the N+N sequences (common name + common name) and N+pN (common name + own name) with a frequency equal to or greater than 18 occurrences. Of the 557 results extracted (24.013 total occurrences) are considered valid 437 (78%2 approximately); the remaining 120 are mainly N+A sequences (name + adjective) or A+N including nominal compounds with adjective3, both with head to the left (pink sweater, judge instructor, leadership group, plan regulator etc.), both with head to right (substitute prosecutor etc.); among the latter, also 1960s, 1990s, 1930s, 1920s, 1940s - classified by the software as sequences with their own names, for the conventional use of capital. The group of 437 sequences potentially useful for the purposes of N+N/N+pN analysis is further reduced, if we eliminate the 14 non-complete sequences (calo respect, tv via, gun calibre, via G, via de...), the 2 adverbial locations (step by step, end) and the 41 foreign loans and Latin expressions (talk show, pole position, week end, par condicio, alter ego, call center, best seller, tour operator etc.). Finally, excluding an appellation - Mr President - and the part of polyrematics - word fine - the whole of the 380 remaining sequences consists of 147 N+N compounds and 231 N+pN sequences, the subject of specific analysis in the next paragraph. As for the first group, they are represented in the compound corpus N+N1 of all categories: endocentric coordinates (decree law) and exocentric (center left), subordinates (press office). Among these, 53 out of 147 sequences are represented by expressions of space or time, formed with few and widespread basic elements (center, middle, morning, afternoon, evening, beginning, end, cardinal points).

Conclusion
The presence of the proper names in the N+pN sequences means that, in most cases, one has to deal with naming relationships with more or less transparent motivation, analyzable, now using the semantics of the elements involved, now, more frequently, using the knowledge of the extra-linguistic world. Completely unrelated to the name, instead, are the sequences of the type EU commissioner, US soldiers that represent for the Italian examples of composition N+pN, alternative to the use of adjectives denominali or prepositional syntagms.
Emojitalianobot and EmojiWorldBot New online tools and digital environments for translation into emoji
Authors: Johanna Monti, Federico Sangati, Francesca Chiusaroli, Matrin Benjamin, Sina Mansour (Università di Napoli L'Orientale, Università di Macerata, EPFL, 2016)
Topic: Sentiment, Emotion, Irony, Hate

Abstract
Emojitalianobot and EmojiWorldBot are two new online tools and digital environments for translation into emoji on Telegram, the popular instant messaging platform. Emojitalianobot is the first open and free Emoji-Italian and Emoji-English translation bot based on Unicode descriptions. The bot was designed to support the translation of Pinocchio into emoji carried out by the followers of the "Scritture brevi" blog on Twitter and contains a glossary with all the uses of emojis in the translation of the famous Italian novel. EmojiWorldBot, an off-spring project of Emojitalianobot, is a multilingual dictionary that uses Emoji as a pivot language from dozens of different languages. Currently the emoji-word and word-emoji functions are available for 72 languages imported from the Unicode tables and provide users with an easy search capability to map words in each of these languages to emojis, and vice versa. This paper presents the projects, the background and the main characteristics of these applications.

Introduction
Emojitalianobot and EmojiWorldBot are two new translation bots into and from emoji. These two bots were designed starting from the hypothesis of setting up an emoji multilingual dictionary and translator through a process of selection and assessment of conventional semantic values. Translation cases may show how images can convey common and universal meanings, beyond specific peculiarities, so as they can stand as models in the perspective of an interlanguage AUTHOR. The two bots ease the use of emojis but also collect, refine and make available valuable linguistic data by means of crowdsourcing and gamification approaches. This contribution presents the state-of-the-art concerning the use of crowdsourcing and gamification approaches to linguistics in section crowd, the Emojitalianobot and the Pinocchio project in section emoji_it, the EmojiWorldBot in section sec:emoji_world and finally conclusions and future work in section conclusions.

Conclusion
We described the Emojitalianobot and theEmojiWorldBot projects. Combining crowdsourcing, gamification and a smartphone app is a powerful strategy to collect, improve and refine valuable linguistic data easily and in a short time particularly for less-resourced languages AUTHOR. These may be the first crowdsourcing projects of this type to use bots for linguistic data collection and validation and are unique in their attempts at engaging participants for different languages.
La leggibilità dei testi di ambito medico rivolti al paziente: il caso dei bugiardini di farmaci senza obbligo di prescrizione medica
Authors: Franca Orletti, Felice Dell'Orletta, Rossella Iovino (Università Roma Tre, CNR-ILC, 2016)
Topic: In-domain IR and IE

Abstract
In this article we present the first results of an exploratory work of analysis and simplification of the leaflets of medicinal products, considered representative texts of medical-patient communication. It will be shown as tools for the automatic treatment of natural language (TAL) can be used to reconstruct the linguistic profile of these texts and to guide their simplification.

Introduction
This contribution aims to address the issue of the linguistic simplification of medical texts addressed directly to patients, as is the case with drug liars without prescription. Despite the official initiatives taken by the AIFA, such as the creation of the Drug Data Bank to help users to use drugs correctly, understanding the benefits and possible side effects, it is known that the language used in these and other medical texts (and not only) is complex and often not adapted to the competences of citizens. This also explains the numerous initiatives for linguistic simplification in the United States and Europe (including Italy) aimed at the linguistic simplification of institutional texts (see, among others, De Mauro 1980, Fioritto 1997, Cortelazzo 1999, De Mauro and Vedovelli 1999, Piemontese 2003, Fortis 2003). In this work, after briefly explaining the main aspects of the complexity of the medical language and presenting the corpus of liars, we will focus on the contribution offered to linguistic simplification by the automatic language treatment tools; in particular, we will refer to the software READ-IT (section 2). The software has been used to monitor (measure the level of readability) some linguistic features of the VIVIN C® liar, chosen because it can be sold without medical prescription (section 2.1). READ-IT can be a valuable help for those who write useful texts: the measurement of the complexity of the text allows rewriting actions in the direction of maximum readability (section 3.2). Finally, conclusions will be outlined (section 4).

Conclusion
This article presents an exploratory work of analysis of a corpus of illustrative leaflets of medicinal products without prescription. The objective was to evaluate the use of TAL tools for monitoring these texts in support of their manual simplification which provides for linguistic interventions aimed at simplifying language at lexical level, with the elimination of technicalities, abstract and deverbal names, and morpho-syntactical, with the preference for the allocation of you and the elimination of nominal, impersonal and passive phrases for the benefit of transitive structures in which both the recovery of the agent and the explication of syntactic relations between the constituent elements of the sentence are easy and accessible to all categories of users.
May the Goddess of Hope Help Us. Homonymy in Latin Lexicon and Onomasticon
Authors: Marco Carlo Passarotti, Marco Budassi (Università Cattolica del Sacro Cuore, Università di Pavia, 2016)
Topic: Latin Resources

Abstract
We present a study on the degree of homonymy between the lexicon of a morphological analyser for Latin and an Onomasticon. To understand the impact of homonymy, we discuss an experiment on four Latin texts of different era and genre.

Introduction
Ambiguity affects linguistic analysis at various levels. In particular, homonymy plays a substantial role in the analysis of single words. Indeed, when considered out of context, one same word can be assigned different Parts of Speech (PoS), morphological features, lemmas and meanings. Contextual disambiguation is the task of Natural Language Processing (NLP) tools like PoS-taggers, morphological analysers, lemmatisers and word-sense disambiguators. The problem of ambiguity is particularly remarkable for NLP when Named Entity Recognition (NER) is concerned. In order to automatically classify the textual occurrences of (multi)words into categories such as names of persons, locations and organisations, NER faces that specific kind of ambiguity consisting in the homonymy between proper names and other words in the lexicon (Nadeau and Sekine, 2007). For instance, the word mark in English can be a proper name, a noun or a verb. Although such homonymy is often tackled by using the upper/lowercase distinction for the initial letter of words, this solution is neither decisive (as uppercase letters can also be motivated by punctuation) nor always available. The latter is especially true for historical languages, as a large amount of texts in such languages comes with no upper/lowercase distinction and it may follow different editorial criteria. The recent extension of the lexical basis of the morphological analyser and lemmatiser for Latin Lemlat with an Onomasticon (i.e. a list of proper names) makes it possible to evaluate the degree of homonymy of proper names in Latin and, thus, to understand the extent of the disambiguation task (Passarotti and Ruffolo, 2004). To this aim, in this paper we explore the lexical basis of Lemlat as providing the empirical evidence supporting our analysis on homonymy between names in the Onomasticon and words in the Latin lexicon.

Conclusion
We presented a study about the degree of homonymy between the lexical basis of a morphological analyser for Latin and an Onomasticon recently added in the tool. We have shown the impact of nominal homonymy on a number of Latin texts of different era and genre. Since the analysis of many homonymous words can be disambiguated according to the features of single texts (and authors), in the near future we foresee to enhance such words in Lemlat with information about their distribution in a number of manually tagged reference texts.
(Better than) State-of-the-Art PoS-tagging for Italian Texts
Authors: Fabio Tamburini (Università di Bologna, 2016)
Topic: Language Models

Abstract
This paper presents some experiments for the construction of an high-performance PoS-tagger for Italian using deep neural networks techniques (DNN) integrated with an Italian powerful morphological analyser. The results obtained by the proposed system on standard datasets taken from the EVALITA campaigns show large accuracy improvements when compared with previous systems from the literature.

Introduction
In recent years there were a large number of works trying to push the accuracy of the PoS-tagging task forward using new techniques, mainly from the deep learning domain AUTHOR. All these studies are mainly devoted to show how to find the best combination of new neural network structures and character/word embeddings for reaching the highest classification performances, and typically present solutions that do not make any use of specific language resources (e.g. morphological analysers, gazetteers, guessing procedures for unknown words, etc.). This is, in general, a very desirable feature because it allows for the production of tools not tied to any specific language, but in various evaluation campaigns, at least for highly-inflected languages as Italian, the results showed quite clearly that this task would benefit from the use of specific and rich language resources AUTHOR. In this study, still work-in-progress, we set-up a PoS-tagger for Italian able to gather the highest classification performances by using any available language resource and the most up-to-date DNN. We used AnIta AUTHOR, one of the most powerful morphological analysers for Italian, based on a wide lexicon (about 110.000 lemmas), for providing the PoS-tagger with a large set of useful information.

Conclusion
The proposed system for PoS-tagging, integrating DNNs and a powerful morphological analyser, exhibited very good accuracy results when applied to standard Italian evaluation datasets from the EVALITA campaigns. The information from AnIta proved to be crucial to reach such accuracy values as well as stacked BiLSTM networks processing entire sentence sequences. We have to further test different DNN configurations and their integration with other kind of PGMs as well as make more experiments with different hyperparameters.
Toward a bilingual lexical database on connectives:,Exploiting a German/Italian parallel corpus
Authors: Peter Bourgonje, Yulia Grishina, Manfred Stede (University of Potsdam, 2017)
Topic: Lexical and Semantic Resources and Analysis

Abstract
We report on experiments to validate and extend two language-specific connective databases (German and Italian) using a word-aligned corpus. This is a first step toward constructing a bilingual lexicon on connectives that are connected via their discourse senses.

Introduction
An important part of discourse processing deals with uncovering coherence relations that hold between individual, ``elementary" units of a text. The lexical items that can signal such a relation are referred to as discourse connectives, and examples of these relations, also called the connectives' senses, are contrast (e.g., `but'), elaboration (e.g., `in particular'), or cause (e.g., `therefore'). Notice, however, that relations need not always be signalled in text, if the context or world knowledge is sufficient for the reader to infer it, as (1)-(4) demonstrate: \item We should hurry, because it's late. \item We should hurry. It's late. \item The red pen costs \2, while the blue one is \2.50. \item The red pen costs \2; the blue one is \2.50. On the other hand, example (6) is a perfectly grammatical sentence but the meaning is different from (5), so for this case of a Concession relation, the connective is in fact indispensable. \item Although it is late, we don't need to hurry. \item It is late; we don't need to hurry. Recognizing these relations, which can hold within a sentence, between two sentences, or between larger spans of text, is a central task for uncovering the structure of a text, as it has been studied in theories like Rhetorical Structure Theory AUTHOR or Segmented Discourse Representation Theory AUTHOR. While the usage of connectives can sometimes be optional, the set of connectives that a language offers is generally taken as important (if not exhaustive) evidence for the set of coherence relations that should be assumed.

Conclusion
We present, to the best of our knowledge, the first Italian–German investigation of discourse connective lexicons. For the subclass of Contrast (in a wide sense), we were able to identify several missing entries in both lexicons, and provided a start on identifying AltLex items for the two languages (future work). Once the information is organized in a complete bilingual database, it can assist translation and conclusions can be drawn regarding connective distribution, sense distribution and ambiguity in the different languages. As prominent steps for future work, we note the disambiguation of connectiveand non-connective readings, the implementation of more sophisticated filtering strategies to retrieve more reliable connective candidates and repeating this study for different languages pairs.
Variabili Rilevanti nella Rappresentazione delle Parole nel Lessico Mentale: Dati Psicolinguistici da una Banca-Dati di Nomi e Verbi Italiani
Authors: Maria De Martino, Azzurra Mancuso, Alessandro Laudanna (Università di Salerno, 2017)
Topic: Lexical and Semantic Resources and Analysis

Abstract
The present paper describes a lexical database containing 100 Italian nouns and 100 Italian verbs. For each noun and verb the database provides information about formal, distributional, semantic, morphological and syntactic characteristics and average recognition times and accuracy. This set of norms is supposed to be helpful in research areas where it is necessary to manipulate and to control for linguistic variables affecting lexical processing of words.

Introduction
Research into lexical processing has shown that many linguistic properties of words affect the way in which they are recognized and produced by speakers. On the other hand, experimentally isolating the role of individual variables is an almost impossible undertaking given the effect of other AUTHOR concurrent variables. In this sense, the availability of descriptive and behavioral databases is crucial in many areas of word processing research. This work is intended to present an operating database and easy to interrogate currently composed of 1 200 Italian words. An innovative aspect of the database is represented by the richness of descriptive parameters for individual words and for the presence of processing measures of the same (average response times and accuracy in a task of visual recognition). This wealth, especially in terms of information on morphological, semantic and syntactic characteristics almost absent in other available research tools, makes the database particularly useful to prepare lists of adequately balanced stimuli for factorial experiments in all areas of research where words can be used as stimuli. A second innovative aspect is the fact that, unlike similar tools available for Italian, the database presented here proposes methods of linguistic analysis and homogeneous classification for the two main classes of words, names and verbs2.

Conclusion
I Verbi Neologici nell’Italiano del Web: Comportamento Sintattico e Selezione dell’Ausiliare
Authors: Matteo Amore (Università di Pavia, 2017)
Topic: Lexical and Semantic Resources and Analysis

Abstract
We analyzed the auxiliary verb selection made by Italian intransitive verbs, purposely by neological verbs. The verbs were chosen from online lists of neologisms. We checked the presence and the behavior of these verbs on the itTenTen corpus. We found that almost all verbs choose the have "have" auxiliary.

Introduction
The aim of this work is to identify the Aid (Aux) selected from the intransitive neological verbs of the Italian language. Before discussing in depth the hypothesis of research, however, it is necessary to present the phenomenon of divided intransitivity, as it constitutes the theoretical background in which this study wants to be inserted.

Conclusion
The clear majority of the neologisms examined select to have as Aux in compound times, while in the presence of the Aux being the participle tends to indicate a state and seems to assume an adjectival value. Such behavior could indicate a propensity, in contemporary Italian, for a clear separation between the functions carried out by the two Aux. Alternatively, preference can be assumed for the creation of V inergatives, over the indictments. As mentioned above (§1.1 and §2.4), this analysis wanted to investigate mainly quantitative aspects, therefore it will necessarily be expanded to determine what are, if any, the reasons for the data found. In particular, the hypotheses concerning the semantic aspect of VNeo will be investigated. An analysis focused on the semantics of the neologisms studied could be useful, in fact, to show any trends in the creation of new verbs (in terms of semantic and/or visual preferences). A further field of investigation worthy of further investigation could be that relating to the values and functions carried out by the past participle in conjunction with the Aux being. Despite the limitations of a broad but subtle notion of neologism and the use of a vast corpus but relative representativeness, the work offers quantitatively clear data confirming the importance of resources such as corporations for the advancement of lexicographic studies (and not only).