pwc-archive/papers-with-abstracts huggingface dataset:
Annotation-based Semantics
Authors: Kiyong Lee
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

This paper proposes a semantics ABS for the model-theoretic interpretation of annotation structures. It provides a language ABSr, that represents \textit{semantic forms} in a (possibly $\lambda$-free) type-theoretic first-order logic. For semantic compositionality, the representation language introduces two operators $\oplus$ and $\oslash$ with subtypes for the conjunctive or distributive composition of semantic forms. ABS also introduces a small set of logical predicates to represent semantic forms in a simplified format. The use of ABSr is illustrated with some annotation structures that conform to ISO 24617 standards on semantic annotation such as ISO-TimeML and ISO-Space.
Annotating Croatian Semantic Type Coercions in CROATPAS
Authors: Costanza Marini, Elisabetta Jezek
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Vocal Bursts Type Prediction

This short research paper presents the results of a corpus-based metonymy annotation exercise on a sample of 101 Croatian verb entries {--} corresponding to 457 patters and over 20,000 corpus lines {--} taken from CROATPAS (Marini {\&} Je{\v{z}}ek, 2019), a digital repository of verb argument structures manually annotated with Semantic Type labels on their argument slots following a methodology inspired by Corpus Pattern Analysis (Hanks, 2004 {\&} 2013; Hanks {\&} Pustejovsky, 2005). CROATPAS will be made available online in 2020. Semantic Type labelling is not only well-suited to annotate verbal polysemy, but also metonymic shifts in verb argument combinations, which in Generative Lexicon (Pustejovsky, 1995 {\&} 1998; Pustejovsky {\&} Je{\v{z}}ek, 2008) are called Semantic Type coercions. From a sub lexical point of view, Semantic Type coercions can be considered as exploitations of one of the qualia roles of those Semantic Types which do not satisfy a verb{'}s selectional requirements, but do not trigger a different verb sense. Overall, we were able to identify 62 different Semantic Type coercions linked to 1,052 metonymic corpus lines. In the future, we plan to compare our results with those from an equivalent study on Italian verbs (Romani, 2020) for a crosslinguistic analysis of metonymic shifts.
A Consolidated Dataset for Knowledge-based Question Generation using Predicate Mapping of Linked Data
Authors: Johanna Melly, Gabriel Luthier, Andrei Popescu-Belis
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Question Generation, Question-Generation

In this paper, we present the ForwardQuestions data set, made of human-generated questions related to knowledge triples. This data set results from the conversion and merger of the existing SimpleDBPediaQA and SimpleQuestionsWikidata data sets, including the mapping of predicates from DBPedia to Wikidata, and the selection of {`}forward{'} questions as opposed to {`}backward{'} ones. The new data set can be used to generate novel questions given an unseen Wikidata triple, by replacing the subjects of existing questions with the new one and then selecting the best candidate questions using semantic and syntactic criteria. Evaluation results indicate that the question generation method using ForwardQuestions improves the quality of questions by about 20{\%} with respect to a baseline not using ranking criteria.
The Annotation of Thematic Structure and Alternations face to the Semantic Variation of Action Verbs. Current Trends in the IMAGACT Ontology
Authors: Massimo Moneglia, Rossella Varvara
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

We present some issues in the development of the semantic annotation of IMAGACT, a multimodal and multilingual ontology of actions. The resource is structured on action concepts that are meant to be cognitive entities and to which a linguistic caption is attached. For each of these concepts, we annotate the minimal thematic structure of the caption and the possible argument alternations allowed. We present some insights on this process with regards to the notion of thematic structure and the relationship between action concepts and linguistic expressions. From the empirical evidence provided by the annotation, we discuss on the very nature of thematic structure, arguing that it is neither a property of the verb itself nor a property of action concepts. We further show what is the relation between thematic structure and 1- the semantic variation of action verbs; 2- the lexical variation of action concepts.
Adapting the ISO 24617-2 Dialogue Act Annotation Scheme for Modelling Medical Consultations
Authors: Volha Petukhova, Harry Bunt
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

Effective, professional and socially competent dialogue of health care providers with their patients is essential to best practice in medicine. To identify, categorize and quantify salient features of patient-provider communication, to model interactive processes in medical encounters and to design digital interactive medical services, two important instruments have been developed: (1) medical interaction analysis systems with the Roter Interaction Analysis System (RIAS) as the most widely used by medical practitioners and (2) dialogue act annotation schemes with ISO 24617-2 as a multidimensional taxonomy of interoperable semantic concepts widely used for corpus annotation and dialogue systems design. Neither instrument fits all purposes. In this paper, we perform a systematic comparative analysis of the categories defined in the RIAS and ISO taxonomies. Overcoming the deficiencies and gaps that were found, we propose a number of extensions to the ISO annotation scheme, making it a powerful analytical and modelling instrument for the analysis, modelling and assessment of medical communication.
Detection and Annotation of Events in Kannada
Authors: Suhan Prabhu, Ujwal Narayan, Alok Debnath, Sumukh S, Manish Shrivastava
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Information Retrieval, Retrieval

In this paper, we provide the basic guidelines towards the detection and linguistic analysis of events in Kannada. Kannada is a morphologically rich, resource poor Dravidian language spoken in southern India. As most information retrieval and extraction tasks are resource intensive, very little work has been done on Kannada NLP, with almost no efforts in discourse analysis and dataset creation for representing events or other semantic annotations in the text. In this paper, we linguistically analyze what constitutes an event in this language, the challenges faced with discourse level annotation and representation due to the rich derivational morphology of the language that allows free word order, numerous multi-word expressions, adverbial participle constructions and constraints on subject-verb relations. Therefore, this paper is one of the first attempts at a large scale discourse level annotation for Kannada, which can be used for semantic annotation and corpus development for other tasks in the language.
Towards the Ontologization of the Outsider Art Domain: Position Paper
Authors: John Roberto, Brian Davis
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: BIG-bench Machine Learning, Cultural Vocal Bursts Intensity Prediction, Position

The purpose of this paper is to present a prospective and interdisciplinary research project seeking to ontologize knowledge of the domain of Outsider Art, that is, the art created outside the boundaries of official culture. The goal is to combine ontology engineering methodologies to develop a knowledge base which i) examines the relation between social exclusion and cultural productions, ii) standardizes the terminology of Outsider Art and iii) enables semantic interoperability between cultural metadata relevant to Outsider Art. The Outsider Art ontology will integrate some existing ontologies and terminologies, such as the CIDOC - Conceptual Reference Model (CRM), the Art {\&} Architecture Thesaurus and the Getty Union List of Artist Names, among other resources. Natural Language Processing and Machine Learning techniques will be fundamental instruments for knowledge acquisition and elicitation. NLP techniques will be used to annotate bibliographies of relevant outsider artists and descriptions of outsider artworks with linguistic information. Machine Learning techniques will be leveraged to acquire knowledge from linguistic features embedded in both types of texts.
Towards Creating Interoperable Resources for Conceptual Annotation of Multilingual Domain Corpora
Authors: Svetlana Sheremetyeva
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Machine Translation, Translation

In this paper we focus on creation of interoperable annotation resources that make up a significant proportion of an on-going project on the development of conceptually annotated multilingual corpora for the domain of terrorist attacks in three languages (English, French and Russian) that can be used for comparative linguistic research, intelligent content and trend analysis, summarization, machine translation, etc. Conceptual annotation is understood as a type of task-oriented domain-specific semantic annotation. The annotation process in our project relies on ontological analysis. The paper details on the issues of the development of both static and dynamic resources such as a universal conceptual annotation scheme, multilingual domain ontology and multipurpose annotation platform with flexible settings, which can be used for the automation of the conceptual resource acquisition and of the annotation process, as well as for the documentation of the annotated corpora specificities. The resources constructed in the course of the research are also to be used for developing concept disambiguation metrics by means of qualitative and quantitative analysis of the golden portion of the conceptually annotated multilingual corpora and of the annotation platform linguistic knowledge.
Infrastructure for the Science and Technology of Language PORTULAN CLARIN
Authors: Ant{\'o}nio Branco, Am{\'a}lia Mendes, Paulo Quaresma, Lu{\'\i}s Gomes, Jo{\~a}o Silva, Andrea Teixeira
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

This paper presents the PORTULAN CLARIN Research Infrastructure for the Science and Technology of Language, which is part of the European research infrastructure CLARIN ERIC as its Portuguese national node, and belongs to the Portuguese National Roadmap of Research Infrastructures of Strategic Relevance. It encompasses a repository, where resources and metadata are deposited for long-term archiving and access, and a workbench, where Language Technology tools and applications are made available through different modes of interaction, among many other services. It is an asset of utmost importance for the technological development of natural languages and for their preparation for the digital age, contributing to ensure the citizenship of their speakers in the information society.
On the Linguistic Linked Open Data Infrastructure
Authors: Christian Chiarcos, Bettina Klimek, Christian F{\"a}th, Thierry Declerck, John Philip McCrae
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

In this paper we describe the current state of development of the Linguistic Linked Open Data (LLOD) infrastructure, an LOD(sub-)cloud of linguistic resources, which covers various linguistic data bases, lexicons, corpora, terminology and metadata repositories.We give in some details an overview of the contributions made by the European H2020 projects {``}Pr{\^e}t-{\`a}-LLOD{''} ({`}Ready-to-useMultilingual Linked Language Data for Knowledge Services across Sectors{'}) and {``}ELEXIS{''} ({`}European Lexicographic Infrastructure{'}) to the further development of the LLOD.
Architecture of a Scalable, Secure and Resilient Translation Platform for Multilingual News Media
Authors: Susie Coleman, Andrew Secker, Rachel Bawden, Barry Haddow, Alex Birch, ra
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Machine Translation, Translation

This paper presents an example architecture for a scalable, secure and resilient Machine Translation (MT) platform, using components available via Amazon Web Services (AWS). It is increasingly common for a single news organisation to publish and monitor news sources in multiple languages. A growth in news sources makes this increasingly challenging and time-consuming but MT can help automate some aspects of this process. Building a translation service provides a single integration point for news room tools that use translation technology allowing MT models to be integrated into a system once, rather than each time the translation technology is needed. By using a range of services provided by AWS, it is possible to architect a platform where multiple pre-existing technologies are combined to build a solution, as opposed to developing software from scratch for deployment on a single virtual machine. This increases the speed at which a platform can be developed and allows the use of well-maintained services. However, a single service also provides challenges. It is key to consider how the platform will scale when handling many users and how to ensure the platform is resilient.
CoBiLiRo: A Research Platform for Bimodal Corpora
Authors: Dan Cristea, Ionu{\textcommabelow{t}} Pistol, {\textcommabelow{S}}erban Boghiu, Anca-Diana Bibiri, Daniela G{\^\i}fu, Andrei Scutelnicu, Mihaela Onofrei, Tr, Diana ab{\u{a}}{\textcommabelow{t}}, George Bugeag
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: speech-recognition, Speech Recognition

This paper describes the on-going work carried out within the CoBiLiRo (Bimodal Corpus for Romanian Language) research project, part of ReTeRom (Resources and Technologies for Developing Human-Machine Interfaces in Romanian). Data annotation finds increasing use in speech recognition and synthesis with the goal to support learning processes. In this context, a variety of different annotation systems for application to Speech and Text Processing environments have been presented. Even if many designs for the data annotations workflow have emerged, the process of handling metadata, to manage complex user-defined annotations, is not covered enough. We propose a design of the format aimed to serve as an annotation standard for bimodal resources, which facilitates searching, editing and statistical analysis operations over it. The design and implementation of an infrastructure that houses the resources are also presented. The goal is widening the dissemination of bimodal corpora for research valorisation and use in applications. Also, this study reports on the main operations of the web Platform which hosts the corpus and the automatic conversion flows that brings the submitted files at the format accepted by the Platform.
CLARIN: Distributed Language Resources and Technology in a European Infrastructure
Authors: Maria Eskevich, Franciska de Jong, Alex K{\"o}nig, er, Darja Fi{\v{s}}er, Dieter van Uytvanck, Tero Aalto, Lars Borin, Olga Gerassimenko, Jan Hajic, Henk van den Heuvel, Neeme Kahusk, Krista Liin, Martin Matthiesen, Stelios Piperidis, Kadri Vider
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

CLARIN is a European Research Infrastructure providing access to digital language resources and tools from across Europe and beyond to researchers in the humanities and social sciences. This paper focuses on CLARIN as a platform for the sharing of language resources. It zooms in on the service offer for the aggregation of language repositories and the value proposition for a number of communities that benefit from the enhanced visibility of their data and services as a result of integration in CLARIN. The enhanced findability of language resources is serving the social sciences and humanities (SSH) community at large and supports research communities that aim to collaborate based on virtual collections for a specific domain. The paper also addresses the wider landscape of service platforms based on language technologies which has the potential of becoming a powerful set of interoperable facilities to a variety of communities of use.
ELRI: A Decentralised Network of National Relay Stations to Collect, Prepare and Share Language Resources
Authors: Thierry Etchegoyhen, Borja Anza Porras, Andoni Azpeitia, Eva Mart{\'\i}nez Garcia, Jos{\'e} Luis Fonseca, Patricia Fonseca, Paulo Vale, Jane Dunne, Federico Gaspari, Teresa Lynn, Helen McHugh, Andy Way, Victoria Arranz, Khalid Choukri, Herv{\'e} Pusset, Alex Sicard, re, Rui Neto, Maite Melero, David Perez, Ant{\'o}nio Branco, Ruben Branco, Lu{\'\i}s Gomes
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Translation

We describe the European Language Resource Infrastructure (ELRI), a decentralised network to help collect, prepare and share language resources. The infrastructure was developed within a project co-funded by the Connecting Europe Facility Programme of the European Union, and has been deployed in the four Member States participating in the project, namely France, Ireland, Portugal and Spain. ELRI provides sustainable and flexible means to collect and share language resources via National Relay Stations, to which members of public institutions can freely subscribe. The infrastructure includes fully automated data processing engines to facilitate the preparation, sharing and wider reuse of useful language resources that can help optimise human and automated translation services in the European Union.
Removing European Language Barriers with Innovative Machine Translation Technology
Authors: Dario Franceschini, Chiara Canton, Ivan Simonini, Armin Schweinfurth, Adelheid Glott, Sebastian St{\"u}ker, Thai-Son Nguyen, Felix Schneider, Thanh-Le Ha, Alex Waibel, Barry Haddow, Philip Williams, Rico Sennrich, Ond{\v{r}}ej Bojar, Sangeet Sagar, Dominik Mach{\'a}{\v{c}}ek, Otakar Smr{\v{z}}
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Machine Translation, Translation

This paper presents our progress towards deploying a versatile communication platform in the task of highly multilingual live speech translation for conferences and remote meetings live subtitling. The platform has been designed with a focus on very low latency and high flexibility while allowing research prototypes of speech and text processing tools to be easily connected, regardless of where they physically run. We outline our architecture solution and also briefly compare it with the ELG platform. Technical details are provided on the most important components and we summarize the test deployment events we ran so far.
Eco.pangeamt: Industrializing Neural MT
Authors: Mercedes Garc{\'\i}a-Mart{\'\i}nez, Manuel Herranz, Am Estela, o, {\'A}ngela Franco, Laurent Bi{\'e}
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Machine Translation, Translation

Eco is Pangeanic{'}s customer portal for generic or specialized translation services (machine translation and post-editing, generic API MT and custom API MT). Users can request the processing (translation) of files in different formats. Moreover, a client user can manage the engines and models allowing their cloning and retraining.
The Kairntech Sherpa -- An ML Platform and API for the Enrichment of (not only) Scientific Content
Authors: Stefan Gei{\ss}ler
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

We present an software platform and API that combines various ML and NLP approaches for the analysis and enrichment of textual content. The platform{'}s design and implementation is guided by the goal to allow non-technical users to conduct their own experiments and training runs on their respective data, allowing to test, tune and deploy analysis models for production. Dedicated specific packages for subtasks such as document structure processing, document categorization, annotation with existing thesauri, disambiguation and linking, annotation with newly created entity recognizers and summarization {--} available as open source components in isolation {--} are combined into an end-user-facing, collaborative, scalable platform to support large-scale industrial document analysis document analysis. We see the Sherpa{'}s setup as an answer to the observation that ML has reached a level of maturity that allows to attain useful results in many analysis scenarios today, but that in-depth technical competencies in the required fields of NLP and AI is often scarce; a setup that focusses on non-technical domain-expert end-users can help to bring required analysis functionalities closer to the day-to-day reality in business contexts.
Towards Standardization of Web Service Protocols for NLPaaS
Authors: Jin-Dong Kim, Nancy Ide, Keith Suderman
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Survey

Several web services for various natural language processing (NLP) tasks ({`}{`}NLP-as-a-service{''} or NLPaaS) have recently been made publicly available. However, despite their similar functionality these services often differ in the protocols they use, thus complicating the development of clients accessing them. A survey of currently available NLPaaS services suggests that it may be possible to identify a minimal application layer protocol that can be shared by NLPaaS services without sacrificing functionality or convenience, while at the same time simplifying the development of clients for these services. In this paper, we hope to raise awareness of the interoperability problems caused by the variety of existing web service protocols, and describe an effort to identify a set of best practices for NLPaaS protocol design. To that end, we survey and compare protocols used by NLPaaS services and suggest how these protocols may be further aligned to reduce variation.
NTeALan Dictionaries Platforms: An Example Of Collaboration-Based Model
Authors: Elvis Mboning, Daniel Baleba, Jean Marc Bassahak, W, Ornella ji, Jules Assoumou
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5
Tasks: Management

Nowadays the scarcity and dispersion of open-source NLP resources and tools in and for African languages make it difficult for researchers to truly fit these languages into current algorithms of artificial intelligence, resulting in the stagnation of these numerous languages, as far as technological progress is concerned. Created in 2017, with the aim of building communities of voluntary contributors around African native and/or national languages, cultures, NLP technologies and artificial intelligence, the NTeALan association has set up a series of web collaborative platforms intended to allow the aforementioned communities to create and manage their own lexicographic and linguistic resources. This paper aims at presenting the first versions of three lexicographic platforms that we developed in and for African languages: the REST/GraphQL API for saving lexicographic resources, the dictionary management platform and the collaborative dictionary platform. We also describe the data representation format used for these resources. After experimenting with a few dictionaries and looking at users feedback, we are convinced that only collaboration-based approaches and platforms can effectively respond to challenges of producing quality resources in and for African native and/or national languages.
A Workflow Manager for Complex NLP and Content Curation Workflows
Authors: Julian Moreno-Schneider, Peter Bourgonje, Florian Kintzel, Georg Rehm
Date: 2020-05-01 00:00:00
Proceeding: LREC 2020 5

We present a workflow manager for the flexible creation and customisation of NLP processing pipelines. The workflow manager addresses challenges in interoperability across various different NLP tasks and hardware-based resource usage. Based on the four key principles of generality, flexibility, scalability and efficiency, we present the first version of the workflow manager by providing details on its custom definition language, explaining the communication components and the general system architecture and setup. We currently implement the system, which is grounded and motivated by real-world industry use cases in several innovation and transfer projects.