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To facilitate corpus searches by classicists as well as to reduce data sparsity when training models, we focus on the automatic lemmatization of ancient Greek inscriptions, which have not received as much attention in this sense as literary text data has. We show that existing lemmatizers for ancient Greek, trained on literary data, are not performant on epigraphic data, due to major language differences between the two types of texts. We thus train the first inscription-specific lemmatizer achieving above 80% accuracy, and make both the models and the lemmatized data available to the community. We also provide a detailed error analysis highlighting peculiarities of inscriptions which again highlights the importance of a lemmatizer dedicated to inscriptions.

The scarcity of parallel data is a major limitation for Neural Machine Translation (NMT) systems, in particular for translation into morphologically rich languages (MRLs). An important way to overcome the lack of parallel data is to leverage target monolingual data, which is typically more abundant and easier to collect. We evaluate a number of techniques to achieve this, ranging from back-translation to random token masking, on the challenging task of translating English into four typologically diverse MRLs, under low-resource settings. Additionally, we introduce Inflection Pre-Training (or PT-Inflect), a novel pre-training objective whereby the NMT system is pre-trained on the task of re-inflecting lemmatized target sentences before being trained on standard source-to-target language translation. We conduct our evaluation on four typologically diverse target MRLs, and find that PT-Inflect surpasses NMT systems trained only on parallel data. While PT-Inflect is outperformed by back-translation overall, combining the two techniques leads to gains in some of the evaluated language pairs.

This article presents the first output of the Dutch FrameNet annotation tool, which facilitates both referential- and frame-annotations of language-independent corpora. On the referential level, the tool links in-text mentions to structured data, grounding the text in the real world. On the frame level, those same mentions are annotated with respect to their semantic sense. This way of annotating not only generates a rich linguistic dataset that is grounded in real-world event instances, but also guides the annotators in frame identification, resulting in high inter-annotator-agreement and consistent annotations across documents and at discourse level, exceeding traditional sentence level annotations of frame elements. Moreover, the annotation tool features a dynamic lexical lookup that increases the development of a cross-domain FrameNet lexicon.

Neural Network (NN) architectures are used more and more to model large amounts of data, such as text data available online. Transformer-based NN architectures have shown to be very useful for language modelling. Although many researchers study how such Language Models (LMs) work, not much attention has been paid to the privacy risks of training LMs on large amounts of data and publishing them online. This paper presents a new method for anonymizing a language model by presenting the way in which MedRoBERTa.nl, a Dutch language model for hospital notes, was anonymized. The two step method involves i) automatic anonymization of the training data and ii) semi-automatic anonymization of the LM's vocabulary. Adopting the fill-mask task where the model predicts what tokens are most probable to appear in a certain context, it was tested how often the model will predict a name in a context where a name should be. It was shown that it predicts a name-like token 0.2% of the time. Any name-like token that was predicted was never the name originally presented in the training data. By explaining how a LM trained on highly private real-world medical data can be safely published with open access, we hope that more language resources will be published openly and responsibly so the community can profit from them.

Topological Data Analysis (TDA) focuses on the inherent shape of (spatial) data. As such, it may provide useful methods to explore spatial representations of linguistic data (embeddings) which have become central in NLP. In this paper we aim to introduce TDA to researchers in language technology. We use TDA to represent document structure as so-called story trees. Story trees are hierarchical representations created from semantic vector representations of sentences via persistent homology. They can be used to identify and clearly visualize prominent components of a story line. We showcase their potential by using story trees to create extractive summaries for news stories.

Can language models read biomedical texts and explain the biomedical mechanisms discussed? In this work we introduce a biomedical mechanism summarization task. Biomedical studies often investigate the mechanisms behind how one entity (e.g., a protein or a chemical) affects another in a biological context. The abstracts of these publications often include a focused set of sentences that present relevant supporting statements regarding such relationships, associated experimental evidence, and a concluding sentence that summarizes the mechanism underlying the relationship. We leverage this structure and create a summarization task, where the input is a collection of sentences and the main entities in an abstract, and the output includes the relationship and a sentence that summarizes the mechanism. Using a small amount of manually labeled mechanism sentences, we train a mechanism sentence classifier to filter a large biomedical abstract collection and create a summarization dataset with 22k instances. We also introduce conclusion sentence generation as a pretraining task with 611k instances. We benchmark the performance of large bio-domain language models. We find that while the pretraining task help improves performance, the best model produces acceptable mechanism outputs in only 32% of the instances, which shows the task presents significant challenges in biomedical language understanding and summarization.

The study of modal verbs in the growing vaccination debate reveals important insights into perspectives on vaccination: must children be vaccinated or are parents allowed not to vaccinate? How strong are the recommendations by pro- and anti-vaccination supporters? We present experimental work on annotation of modal verbs and their senses in texts related to the vaccination debate, as well as the resulting corpus. The results from our pilot study suggest that the most frequent type of modality was epistemic - indicating that participants in the debate appear to be more concerned with the safety and efficacy of vaccines than with moral arguments. Those against vaccination appear to be more committed or convinced of their views than those in favor, as evidenced by the use of the modal must.

In this paper we present the Vaccination Corpus, a corpus of texts related to the online vaccination debate that has been annotated with three layers of information about perspectives: attribution, claims and opinions. Additionally, events related to the vaccination debate are also annotated. The corpus contains 294 documents from the Internet which reflect different views on vaccinations. It has been compiled to study the language of online debates, with the final goal of experimenting with methodologies to extract and contrast perspectives within the vaccination debate.

In this work we address the processing of negation in Spanish. We first present a machine learning system that processes negation in Spanish. Specifically, we focus on two tasks: i) negation cue detection and ii) scope identification. The corpus used in the experimental framework is the SFU ReviewSP-NEG. The results for cue detection outperform state-of-the-art results, whereas for scope detection this is the first system that performs the task for Spanish. Moreover, we provide a qualitative error analysis aimed at understanding the limitations of the system and showing which negation cues and scopes are straightforward to predict automatically, and which ones are challenging.

In this paper, we introduce a new type of shared task - which is collaborative rather than competitive - designed to support and foster the reproduction of research results. We also describe the first event running such a novel challenge, present the results obtained, discuss the lessons learned and ponder on future undertakings.

Given the limited size of existing idiom corpora, we aim to enable progress in automatic idiom processing and linguistic analysis by creating the largest-to-date corpus of idioms for English. Using a fixed idiom list, automatic pre-extraction, and a strictly controlled crowdsourced annotation procedure, we show that it is feasible to build a high-quality corpus comprising more than 50K instances, an order of a magnitude larger than previous resources. Crucial ingredients of crowdsourcing were the selection of crowdworkers, clear and comprehensive instructions, and an interface that breaks down the task in small, manageable steps. Analysis of the resulting corpus revealed strong effects of genre on idiom distribution, providing new evidence for existing theories on what influences idiom usage. The corpus also contains rich metadata, and is made publicly available.

An important objective in health-technology is the ability to gather information about people's well-being. Structured interviews can be used to obtain this information, but these are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, yet they typically lack depth. In this paper, we present our first prototype of the Behaviour-based Language-Interactive Speaking Systems (BLISS), an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of BLISS is to understand the motivations behind people's happiness by conducting a personalized spoken dialogue based on a happiness model. We built our first prototype of the model to collect 55 spoken dialogues, in which the BLISS agent asked questions to users about their happiness and well-being. Apart from a description of the BLISS architecture, we also provide details about our dataset, which contains mentions of over 120 activities and 100 motivations and is made available for usage.

In this paper, we describe the Circumstantial Event Ontology (CEO), a newly developed ontology for calamity events that models semantic circumstantial relations between event classes, where we define circumstantial as inferred implicit causal relations. The circumstantial relations are inferred from the assertions of the event classes that involve a change to the same property of a participant. Our model captures that the change yielded by one event, explains to people the happening of the next event when observed. We describe the meta model and the contents of the ontology, the creation of a manually annotated corpus for circumstantial relations based on ECB+ and the first results on the evaluation of the ontology.

It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.

Research from communication science has shown that stereotypical ideas are often reflected in language use. Media coverage of different groups in society influences the perception people have about these groups and even increases distrust and polarization among different groups. Investigating the forms of (especially subtle) stereotyping can raise awareness to journalists and help prevent reinforcing oppositions between groups in society. Conducting large-scale, deep investigations to determine whether we are faced with stereotyping is time-consuming and costly. We propose to tackle this challenges through the means of microportraits: an impression of a target group or individual conveyed in a single text. We introduce the first system implementation for Dutch and show that microportraits allow social scientists to explore various dimensions of stereotyping. We explore the possibilities provided by microportraits by investigating stereotyping of Muslims in the Dutch media. Our (preliminary) results show that microportraits provide more detailed insights into stereotyping compared to more basic models such as word clouds.

In this article we review Temporal Processing systems that participated in the TempEval-3 task as a basis to develop our own system, that we also present and release. The system incorporates high level lexical semantic features, obtaining the best scores for event detection (F1-Class 72.24) and second best result for temporal relation classification from raw text (F1 29.69) when evaluated on the TempEval-3 data. Additionally, we analyse the errors of all TempEval-3 systems for which the output is publicly available with the purpose of finding out what are the weaknesses of current approaches. Although incorporating lexical semantics features increases the performance of our system, the error analysis shows that systems should incorporate inference mechanisms and world knowledge, as well as having strategies to compensate for data skewness.

We focused on building a corpus constituted by the query logs registered by the GreyGuide: Repository and Portal to Good Practices and Resources in Grey Literature and received by the WorldWideScience.org (The Global Science Gateway) portal: the aim is to retrieve information related to social media which as of today represent a considerable source of data more and more widely used for research ends. This project includes eight months of query logs3 registered between July 2017 and February 2018 for a total of 445,827 queries. The analysis mainly concentrates on the semantics of the queries received from the portal clients: it is a process of information retrieval from a rich digital catalogue whose language is dynamic, is evolving and follows - as well as reflects - the cultural changes of our modern society.

Systematic reviews in e.g. empirical medicine address research questions by comprehensively examining the entire published literature. Conventionally, manual literature surveys decide inclusion in two steps, first based on abstracts and title, then by full text, yet current methods to automate the process make no distinction between gold data from these two stages. In this work we compare the impact different schemes for choosing positive and negative examples from the different screening stages have on the training of automated systems. We train a ranker using logistic regression and evaluate it on a new gold standard dataset for clinical NLP, and on an existing gold standard dataset for drug class efficacy. The classification and ranking achieves an average AUC of 0.803 and 0.768 when relying on gold standard decisions based on title and abstracts of articles, and an AUC of 0.625 and 0.839 when relying on gold standard decisions based on full text. Our results suggest that it makes little difference which screening stage the gold standard decisions are drawn from, and that the decisions need not be based on the full text. The results further suggest that common-off-the-shelf algorithms can reduce the amount of work required to retrieve relevant literature.

This paper (1) presents the first partially manually verified treebank for Dutch CHILDES corpora, the AnnCor CHILDES Treebank; (2) argues explicitly that it is useful to assign adult grammar syntactic structures to utterances of children who are still in the process of acquiring the language; (3) argues that human annotation and automatic checks on this annotation must go hand in hand; (4) argues that explicit annotation guidelines and conventions must be developed and adhered to and emphasises consistency of the annotations as an important desirable property for annotations. It also describes the tools used for annotation and automated checks on edited syntactic structures, as well as extensions to an existing treebank query application (GrETEL) and the multiple formats in which the resources will be made available

It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.

This paper (1) presents the first partially manually verified treebank for Dutch CHILDES corpora, the AnnCor CHILDES Treebank; (2) argues explicitly that it is useful to assign adult grammar syntactic structures to utterances of children who are still in the process of acquiring the language; (3) argues that human annotation and automatic checks on this annotation must go hand in hand; (4) argues that explicit annotation guidelines and conventions must be developed and adhered to and emphasises consistency of the annotations as an important desirable property for annotations. It also describes the tools used for annotation and automated checks on edited syntactic structures, as well as extensions to an existing treebank query application (GrETEL) and the multiple formats in which the resources will be made available

Implicit Semantic Role Labeling is a challenging task: it requires high-level understanding of the text while annotated data is very limited. Due to the lack of training data, most researches either resort to simplistic machine learning methods or focus on automatically acquiring training data. In this paper, we explore the possibilities of using more complex and expressive machine learning models trained on a large amount of explicit roles. In addition, we compare the impact of one-way and multi-way selectional preference with the hypothesis that the added information in multi-way models are beneficial. Although our models surpass a baseline that uses prototypical vectors for SemEval-2010, we otherwise face mostly negative results. Selectional preference models perform lower than the baseline on ON5V, a dataset of five ambiguous and frequent verbs. They are also outperformed by the Naive Bayes model of Feizabadi and Pado (2015) on both datasets. We conclude that, even though multi-way selectional preference improves results for predicting explicit semantic roles compared to one-way selectional preference, it harms performance for implicit roles. We release our source code, including the reimplementation of two previously unavailable systems to enable further experimentation.

With the continuous growth of benchmark corpora, which often annotate the same documents, there is a range of opportunities to compare and combine similar and complementary annotations. However, these opportunities are hampered by a wide range of problems that are related to the lack of resource interoperability. In this paper, we illustrate these problems by assessing aspects of interoperability at the document-level across a set of 20 corpora annotated with (aspects of) events. The issues range from applying different document naming conventions, to mismatches in textual content and structural/conceptual differences among annotation schemes. We provide insight into the exact document intersections between the corpora by mapping their document identifiers and perform an empirical analysis of event annotations showing their compatibility and consistency in and across the corpora. This way, we aim to make the community more aware of the challenges and opportunities and to inspire working collaboratively towards interoperable resources.

In this paper, we present a new method to obtain large volumes of high-quality text corpora with event data for studying identity and reference relations. We report on the current methods to create event reference data by annotating texts and deriving the event data a posteriori. Our method starts from event registries in which event data is defined a priori. From this data, we extract so-called Microworlds of referential data with the Reference Texts that report on these events. This makes it possible to easily establish referential relations with high precision and at a large scale. In a pilot, we successfully obtained data from these resources with extreme ambiguity and variation, while maintaining the identity and reference relations and without having to annotate large quantities of texts word-by-word. The data from this pilot was annotated using an annotation tool created specifically in order to validate our method and to enrich the reference texts with event coreference annotations. This annotation process resulted in the Gun Violence Corpus, whose development process and outcome are described in this paper.

Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International

Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International

This quotation stresses the important role of the several international organizations in producing and disseminating knowledge in the field of Grey Literature (GL): the paper aims to provide a first snapshot of the geographical distribution of GL organizations and their participation to the annual International Conference on Grey Literature over the time (in the period from 2003 to 2015. See List of Conferences on Table 2 ). Nowadays a visual representation of data is often associated with the traditional statistical graphs, in particular for representing complex phenomena by means of maps and diagrams, which allow a deeper and more focused analysis of the data. In our case the geographical representation of stakeholders in government, academics, business and industry aims at visualizing the GL community across the globe: it concerns 674 organizations which over the years have contributed to the development of a common vision on the most pressing issues of the field by using new paradigms such as Open Access and the social networks.

CLiC-it 2015 is held in Trento on December 3-4 2015, hosted and locally organized by Fondazione Bruno Kessler (FBK), one the most important Italian research centers for what concerns CL. The organization of the conference is the result of a fruitful conjoint effort of different research groups (Università di Torino, Università di Roma Tor Vergata and FBK) showing the nationwide spreading of CL in Italy. As in the first edition, the main aim of the event is at establishing a reference forum on CL, covering all the aspects needed to describe the multi-faceted and cross-disciplinary reality of the involved research topics and of the Italian community working in this area. Indeed the spirit of CLiC-it is inclusive, in order to build a scenario as much as possible comprehensive of the complexity of language phenomena and approaches to address them, bringing together researchers and scholars with different competences and skills and working on different aspects according to different perspectives. The large number of researchers that have decided to present their work at CLiC-it and the number of directions here investigated are proof of the maturity of our community and a promising indication of its vitality. We received a total of 64 paper submissions, out of which 52 have been accepted to appear in the Conference Proceedings, which are available online and on the OpenEdition platform. Overall, we collected 129 authors from 15 countries.

The paper describes experimental dialogue data collection activities, as well semantically annotated corpus creation undertaken within EU-funded METALOGUE project. The project aims to develop a dialogue system with flexible dialogue management to enable systems adaptive, reactive, interactive and proactive dialogue behaviour in setting goals, choosing appropriate strategies and monitoring numerous parallel interpretation and management processes. To achieve these goals negotiation (or more precisely multi-issue bargaining) scenario has been considered as the specific setting and application domain. The dialogue corpus forms the basis for the design of task and interaction models of participants negotiation behaviour, and subsequently for dialogue system development which would be capable to replace one of the negotiators. The METALOGUE corpus will be released to the community for research purposes.

Here we present the final results of the MAPS (Marine Planning and Service Platform) project, an environment designed for gathering, classifying, managing and accessing marine scientific literature and data, making it available for search to Operative Oceanography researchers of various institutions by means of standard protocols. The system takes as input non-textual data (measurements) and text - both published papers and documentation - and it provides an advanced search facility thanks to the rich set of metadata and, above all, to the possibility of a refined and domain targeted key-word indexing of texts using Natural Language Processing (NLP) techniques. The paper describes the system in its details providing also evidence of evaluation. Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International

The work measures grey citations in the years 2012, 2013 and 2014 and then describes the features of GL documents cited in different areas of knowledge: Computational Linguistics, Computer Science and Engineering. With the aim of surveying a wide and varied range of resources, we selected a sample data based on the bibliographical references of articles contained in four journals - all indexed by Scopus Citation Database and ISI Web of Science, with an Impact Factor (IF) over the last three years - and two proceedings of international conferences held in 2012 and 2014. Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International

"When we read the articles or papers of a particular domain, we can recognize some lexical items in the texts as technical terms. In a domain where new knowledge is generated, new terms are constantly created to fulfil the needs of the domain, while others become obsolete. In addition, existing terms may undergo changes of meaning..." (Kageura K.,1998/1999). According to Kaugera, our aim with this work is to make a "journey" in the Grey Literature (GL) domain in order to offer an overall vision on the terms used and the links" "between them. Moreover, by performing a terminological comparison over a given period of time it could be possible to trace the presence of obsolete words as well as of neologisms in the most recent research fields.Within this scenario, the work analyzes a corpus constituted of the entire amount of full" "research papers published in the GL conference series over a time span of more than one decade (2003-2014) with the aim of creating a terminological map of relevant words. "... corpora used to extract terminological units can be further investigated to find semantic and conceptual information on terms or to represent conceptual relationships between terms. (Bourigault D. et al., 2001). Another interesting inquiry is the terminology used in the GL conferences for describing the types of documents (Pej?ová P. et al., 2012). The work is split up in four sections: creation of the corpus by acquiring the digital papers of GL conference proceedings (GL5 - GL16)1; data cleaning; data processing; terminological" "analysis and comparison. The corpus - made up of 231 research papers (for a total amount of 785.042 tokens) - was processed using a Natural Language Processing (NLP) tool for term extraction developed at the Institute of Computational Linguistics "Antonio Zampolli" of CNR (Goggi et al. 2015; 2016). This tool is what is called a "pipeline" (that is, a sequence of different tools) which extracts lexical knowledge from texts: in short, this is a rule system tool for knowledge extraction and document indexing that combines NLP technologies for term extraction and techniques to measure the associative strength of multi-words. This tool extracts a list of single (monograms) and multi-word terms (bigrams and trigrams) ordered by frequency with respect to the context. The pipeline - used as semantic engine within the MAPS project - has been customized for the extraction of terms from our corpus. This survey on the results of the information extraction process performed by the described NLP tool has been a sort of linguistic path in the past and present of terminology used in GL proceedings. By means of samplings, it has been possible to obtain the terminological flow in GL domain and to determine if and how the lexicon was evolving over these twelve years and investigate on its dynamic nature.

Here we present the final results of MAPS (Marine Planning and Service Platform), an environment designed for gathering, classifying, managing and accessing marine scientific literature and data, making it available for search to Operative Oceanography researchers of various institutions by means of standard protocols. In previous publications the general architecture of the system as well as the set of metadata (Common Data Index) used to describe the documents were presented [3]; it was shown how individual oceanographic data-sets could be indexed within the MAPS library by types of measure, measurement tools, geographic areas, and also linked to specific textual documentation. Documentation is described using the current international standards: Title, Authors, Publisher, Language, Date of publication, Body/Institution, Abstract, etc.; serial publications are described in terms of ISSN, while books are assigned ISBN; content of various types on electronic networks is described by means of doi and url. Each description is linked to the document. Thanks to this, the MAPS library already enables researchers to go from structured oceanographic data to documents describing it. But this was not enough: documents may contain important information that has not been encoded in the metadata. Thus an advanced Search Engine was put in place that uses semantic-conceptual technologies in order to extract key concepts from unstructured text such as technical documents (reports and grey literature) and scientific papers and to make them indexable and searchable by the end user in the same way as the structured data (such as oceanographic observations and metadata) is. More specifically once a document is uploaded in the MAPS library, key domain concepts in documents are extracted via a natural language processing pipeline and used as additional information for its indexing. The key term identification algorithm is based on marine concepts that were pre-defined in a domain ontology, but crucially it also allows for the discovery of new related concepts. So for instance starting from the domain term salinity, related terms such as sea salinity and average sea salinity will also be identified as key terms and used for indexing and searching documents. A hybrid search system is then put in place, where users can search the library by metadata or by free text queries. In the latter case, the NLP pipeline performs an analysis of the text of the query, and when key concepts are matched, the relevant documents are presented. The results may be later refined by using other structured information (e.g. date of publication, area, ...). Currently a running system has been put in place, with data from satellites, buoys and sea stations; such data is documented and searchable by its relevant metadata and documentation. Results of quantitative evaluation in terms of information retrieval measures will be presented in the poster; more specifically, given an evaluation set defined by domain experts and composed of pre-defined queries together with documents that answer such queries, it will be shown how the system is highly accurate in retrieving the correct documents from the library. Though this work focuses on oceanography, its results may be easily extended to other domains; more generally, the possibility of enhancing the visibility and accessibility of grey literature via its connection to the data it describes and to an advanced full text indexing are of great relevance for the topic of this conference.

This paper presents the Event and Implied Situation Ontology (ESO), a manually constructed resource which formalizes the pre and post situations of events and the roles of the entities affected by an event. The ontology is built on top of existing resources such as WordNet, SUMO and FrameNet. The ontology is injected to the Predicate Matrix, a resource that integrates predicate and role information from amongst others FrameNet, VerbNet, PropBank, NomBank and WordNet. We illustrate how these resources are used on large document collections to detect information that otherwise would have remained implicit. The ontology is evaluated on two aspects: recall and precision based on a manually annotated corpus and secondly, on the quality of the knowledge inferred by the situation assertions in the ontology. Evaluation results on the quality of the system show that 50% of the events typed and enriched with ESO assertions are correct.

The following title was published on an influential Italian newspaper, La Stampa, on November 7, 2013. “Tra i tesori della ‘Letteratura Grigia’ un’Eneide in napoletano del ‘600”. The article is about the presentation of the “Fondo De Mauro” on the Italian Network of Popular Culture: this fund originates from a private collection built up in several decades and donated to the Network by Tullio De Mauro and his wife Silvana Ferreri in 2011; it is made up of thousands of books, brochures, pamphlets relating to Italian dialects and minority languages. In the field of healthcare, while browsing on the web, we found the title of a PhD thesis of last year: “Letteratura Grigia nelle meta-analisi delle prove ripartite con scelta casuale degli interventi di sanità”. In the legal environment, the title of a Seminar at the University of Siena emerges from the web: “La “centralità” della legge e la letteratura grigia. Profili di politica del diritto in Italia tra Otto e Novecento” . From these findings, the idea of a survey on the wide variety of grey material available on Italian web portals arose. A first analysis showed that this material is available in different forms and dissemination is carried out through various means such as thematic bibliographies, newspapers articles, various types of documents published in PDF format or simple descriptions on web sites. The following are a few examples excerpted from some home pages belonging to our corpus: - Collection of grey literature. The Historical Archive of Women candidates for becoming the repository where the memories about these themes will be stored… - Grey literature ... Master copies · Reprints · Unreleased copies · Grey Literature. Archives for the history of Education… - Grey literature. The high quality brand of parks… - … International grey literature; national and international legislative data on the topic of drug addiction and related themes; documentary archive ... - Besides literature in German, there is literature in other languages and grey literature as well – in particular catalogues of museums and exhibitions… - It is about a few thousand of books, brochures and documents of grey literature concerning two topics, Italian dialects and minority languages… Given this scenario, the research aims at verifying whether – and eventually how much – the grey literature available on the web is actually structured, accessible or even managed by systems dealing with its organization and aiming at its retrieval and storing. The utmost goal is to build up a map of non-academic communities and their mechanisms for managing, presenting and disseminating this type of material. It is a sort of journey among the streams of the Web which channel meeting minutes, invites, manifests, fliers, pictures, newspapers articles, journalistic services and audio/video material on various topics. These “grey” products – by conveying basic information about social and popular culture – store, represent and spread knowledge. Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International

The MAPS (Marine Planning and Service Platform) project is a development of the Marine project (Ricerca Industriale e Sviluppo Sperimentale Regione Liguria 2007-2013) aiming at building a computer platform for supporting a Marine Information and Knowledge System, as part of the data management activities. One of the main objective of the project is to develop a repository that should gather, classify and structure marine scientific literature and data thus guaranteeing their accessibility to researchers and institutions by means of standard protocols. We will present the scenario of the Operative Oceanography together with the technologies used to develop an advanced search engine which aims at providing rapid and efficient access to a Digital Library of oceanographic data. The case-study is also highlighting how the retrieval of grey literature from this specific marine community could be reproduced for similar communities as well, thus revealing the great impact that the processing, re-use as well as application of grey data have on societal needs/problems and their answers. Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International

The MAPS (Marine Planning and Service Platform) project is a development of the Marine project (Ricerca Industriale e Sviluppo Sperimentale Regione Liguria 2007-2013) aiming at building a computer platform for supporting Operative Oceanography in its activities. One of the main objective of the project is to develop a repository that should gather, classify and structure marine scientific literature and data thus guaranteeing their accessibility to researchers and institutions by means of standard protocols. Community and Requirements. Operative Oceanography is the branch of marine research which deals with the development of integrated systems for examining and modeling the ocean monitoring and forecast. Experts need access to real-time data on the state of the sea such as forecasts on temperatures, streams, tides and the relevant scientific literature. This finds application in many areas, ranging from civilian and military safety to protection of off-shore and coastal infrastructures. The metadata. The set of metadata associated with marine data is defined in the CDI (Common Data Index) documented standard. They encode: the types of sizes which have been measured; the measurement tools the platform which has been employed; the geographic area where measures have been taken; the environmental matrix; the descriptive documentation. As concerns the scientific documentation, at the current stage of the CDI standard, a document is shaped around the following metadata: Title, Authors, Version, ISBN/DOI, Topic, Date of publication, Body/Institution, Abstract. The search engine. The query system (which is actually under development) has been designed for operating with structured data - the metadata - and raw data - the associated technical and scientific documentation. Full-text technologies are often unsuccessful when applied to this type of queries since they assume the presence of specific keywords in the text; in order to fix this problem, the MAPS project suggests to use different emantic technologies for retrieving the text and data and thus getting much more complying results. In the Poster we will present the scenario of the Operative Oceanography together with the technologies used to develop an advanced earch engine which aims at providing rapid and efficient access to a Digital Library of oceanographic data. The case-study is also highlighting how the retrieval of grey literature from this specific marine community could be reproduced for similar communities as well, thus revealing the 2 great impact that the processing, re-use as well as application of grey data have on societal needs/problems and their answers.

The following title was published on an influential Italian newspaper, La Stampa, on November 7, 2013. "Tra i tesori della 'Letteratura Grigia' un'Eneide in napoletano del '600". The article is about the presentation of the "Fondo De Mauro" on the Italian Network of Popular Culture: this fund originates from a private collection built up in several decades and donated to the Network by Tullio De Mauro and his wife Silvana Ferreri in 2011; it is made up of thousands of books, brochures, pamphlets relating to Italian dialects and minority languages. In the field of healthcare, while browsing on the web, we found the title of a PhD thesis of last year: "Letteratura Grigia nelle meta-analisi delle prove ripartite con scelta casuale degli interventi di sanità". In the legal environment, the title of a Seminar at the University of Siena emerges from the web: "La "centralità" della legge e la letteratura grigia. Profili di politica del diritto in Italia tra Otto e Novecento" . From these findings, the idea of a survey on the wide variety of grey material available on Italian web portals arises. A first analysis shows that this material is available in different forms and dissemination is carried out through various means such as thematic bibliographies, newspapers articles, various types of documents published in pdf format or simple descriptions on web sites. The following are a few examples excerpted from some home pages belonging to our corpus: ? Collection of grey literature. The Historical Archive of Women candidates for becoming the repository where the memories about these themes will be stored... ? Grey literature ... Master copies · Reprints · Unreleased copies · Grey Literature. Archives for the history of Education... ? Grey literature. The high quality brand of parks... ? ... International grey literature; national and international legislative data on the topic of drug addiction and related themes; documentary archive ... ? Besides literature in German, there is literature in other languages and grey literature as well - in particular catalogues of museums and exhibitions... ? It is about a few thousand of books, brochures and documents of grey literature concerning two topics, Italian dialects and minority languages... Given this scenario, the research aims at verifying whether - and eventually how much - the grey literature available on the web is actually structured, accessible or even managed by systems dealing with its organization and aiming at its retrieval and storing. The utmost goal is to build up a map of non-academic communities and their mechanisms for managing, presenting and disseminating this type of material: a sort of journey among the streams of the web which channel meeting minutes, invites, manifests, fliers, pictures, newspapers articles, journalistic services and audio/video material on various topics. These "grey" products - by conveying basic information about social and popular culture - store, represent and spread knowledge. Significant examples could be identified in the web sites presenting the following matters: history of women's culture and of their movement in some specific Italian regions; projects dealing with the sustainability of urban environment with respect to childhood and adolescence; parks and other natural protected environments; archaeological documentation such as draft reports, diaries from the site, letters and miscellaneous documentation; nursing and health-related disciplines which produce guidelines, diagnostic and therapeutic courses, informative material for patients and their families. Also the theatrical culture is nourished by "grey products" as video archives, collections of music LPs and CDs, brochures, scripts, autograph manuscripts (i.e.. letters, correspondences, fliers, musical scores). In substance, a heterogeneous set of material which could reveal especially interesting to both researchers, scientists, professionals and simple fans and lovers of the various subjects if ever made available and usable. Focus Analysis of the documentation and production of taxonomies finalized at the creation of a map of non-academic communities and stakeholders involved in the management of grey material. Material and methods The survey examines the several disciplines, the typology, the institutional nature and the fields to which these grey communities belong, noticing as well the variety of documentation provided, the structure of information and the presentation and access modalities through the following steps: 1) Selection of the web portals as resulted from the query "letteratura grigia" OR "letteratura non convenzionale" OR "documentazione grigia" OR "materiale grigio". 2) Creation of a corpus made up of 28,000 occurrences. 3) Analysis of the various communities and of the grey material retrieved. 4) Statistical elaboration of the data. Conclusions: reflections on the communities and stakeholders involved in the management of grey literature and on the various ways of presenting the documentation provided by the web sites selected for this survey.

The survey is focused on the documentation produced by the European Commission (EC) projects involved in the Framework Programme for Research and Technological Development (hereafter FP7) and managed by the Italian National Research Council (hereafter CNR). In particular, the Grey Literature (GL) available on CORDIS1 and European Projects websites was analysed. In order to verify how it is managed and whether it is compliant with EC recommendations, some categories were introduced to identify, measure and evaluate the usability and availability of projects production. Data was obtained from a sample of European projects websites. Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International

Both sentiment and event factuality are fundamental information levels for our understanding of events mentioned in news texts. Most research so far has focused on either modeling opinions or factuality. In this paper, we propose a model that combines the two for the extraction and interpretation of perspectives on events. By doing so, we can explain the way people perceive changes in (their belief of) the world as a function of their fears of changes to the bad or their hopes of changes to the good. This study seeks to examine the effectiveness of this approach by applying factuality annotations, based on FactBank, on top of the MPQA Corpus, a corpus containing news texts annotated for sentiments and other private states. Our findings suggest that this approach can be valuable for the understanding of perspectives, but that there is still some work to do on the refinement of the integration.

The survey is focused on the documentation produced by the European Commission (EC) projects involved in the Framework Programme for Research and Technological Development (hereafter FP7) and managed by the Italian National Research Council (hereafter CNR). In particular, the Grey Literature (GL) available on CORDIS1 and European Projects websites was analysed. In order to verify how it is managed and whether it is compliant with EC recommendations, some categories were introduced to identify, measure and evaluate the usability and availability of projects production. Data was obtained from a sample of European projects websites.

The European project NewsReader develops technology to process daily news streams in 4 languages, extracting what happened, when, where and who was involved. NewsReader does not just read a single newspaper but massive amounts of news coming from thousands of sources. It compares the results across sources to complement information and determine where they disagree. Furthermore, it merges news of today with previous news, creating a long-term history rather than separate events. The result is stored in a KnowledgeStore, that cumulates information over time, producing an extremely large knowledge graph that is visualized using new techniques to provide more comprehensive access. We present the first version of the system and the results of processing first batches of data.

The aim of this paper is to introduce the Open Access movement for Natural Language Processing (NLP) by means of a wide range of open access Grey Literature documentation available on the web. In 2008 Robert Dale, in the last issue of volume 35 of Computational Linguistics said: "There are a number of definitions of the term 'open access' in circulation, but almost all share the key principle that scientific literature should be freely available for all to read, download, copy, distribute, and use (with appropriate attribution) without restriction". At first glance it might seem that the Open Access movement has gradually become more influential in the field of language technology by building repositories accessible through the network. Today's digital archives are niches of intellectual production spread by means of a wide range of documents (such as journal articles and proceedings) which, paradoxically, the search engines do not always reach. The use of inappropriate terms in the formulation of queries and the fragmentation of repositories in this area of investigation does not allow to retrieve information on a large scale. The full paper, after a first introductory section, will be organized in two sections: 1) the first dedicated to the methodology for searching and tracing open access resources and to the criteria for analyzing and selecting the online documentation; 2) the second devoted to a description of the state-of-the-art of Open Access Grey Literature material in a statistical and thematic scenario. As things stand, standardization of computational systems interconnected by links and tools of various nature allowing Internet users to easily retrieve the information that the web naturally makes available would then be essential. Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International

Sommario in IngleseThe aim of this paper is to introduce the Open Access movement for Natural Language Processing (NLP) by means of a wide range of open access Grey Literature documentation available on the web. In 2008 Robert Dale, in the last issue of volume 35 of Computational Linguistics said: "There are a number of definitions of the term 'open access' in circulation, but almost all share the key principle that scientific literature should be freely available for all to read, download, copy, distribute, and use (with appropriate attribution) without restriction". At first glance it might seem that the Open Access movement has gradually become more influential in the field of language technology by building repositories accessible through the network. Today's digital archives are niches of intellectual production spread by means of a wide range of documents (such as journal articles and proceedings) which, paradoxically, the search engines do not always reach. The use of inappropriate terms in the formulation of queries and the fragmentation of repositories in this area of investigation does not allow to retrieve information on a large scale. The full paper, after a first introductory section, will be organized in two sections: 1) the first dedicated to the methodology for searching and tracing open access resources and to the criteria for analyzing and selecting the online documentation; 2) the second devoted to a description of the state-of-the-art of Open Access Grey Literature material in a statistical and thematic scenario. As things stand, standardization of computational systems interconnected by links and tools of various nature allowing Internet users to easily retrieve the information that the web naturally makes available would then be essential. Topics: Sustainability, Public Accessible Resources, Product and Service enhancements, Open Access, Curation and Preservation

This study wants to explore new ways of social media communication for Grey Literature. In particular it describes the role of social media in relation with traditional channels and how social media applications can be used for Grey. Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notes XA International