pwc-archive/papers-with-abstracts huggingface dataset:
A Large-scale Recipe and Meal Data Collection as Infrastructure for Food Research
Authors: Jun Harashima, Michiaki Ariga, Kenta Murata, Masayuki Ioki
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

Everyday meals are an important part of our daily lives and, currently, there are many Internet sites that help us plan these meals. Allied to the growth in the amount of food data such as recipes available on the Internet is an increase in the number of studies on these data, such as recipe analysis and recipe search. However, there are few publicly available resources for food research; those that do exist do not include a wide range of food data or any meal data (that is, likely combinations of recipes). In this study, we construct a large-scale recipe and meal data collection as the underlying infrastructure to promote food research. Our corpus consists of approximately 1.7 million recipes and 36000 meals in cookpad, one of the largest recipe sites in the world. We made the corpus available to researchers in February 2015 and as of February 2016, 82 research groups at 56 universities have made use of it to enhance their studies.
EstNLTK - NLP Toolkit for Estonian
Authors: Siim Orasmaa, Timo Petmanson, Alex Tkachenko, er, Sven Laur, Heiki-Jaan Kaalep
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Morphological Analysis, named-entity-recognition, Named Entity Recognition, Named Entity Recognition (NER)

Although there are many tools for natural language processing tasks in Estonian, these tools are very loosely interoperable, and it is not easy to build practical applications on top of them. In this paper, we introduce a new Python library for natural language processing in Estonian, which provides unified programming interface for various NLP components. The EstNLTK toolkit provides utilities for basic NLP tasks including tokenization, morphological analysis, lemmatisation and named entity recognition as well as offers more advanced features such as a clause segmentation, temporal expression extraction and normalization, verb chain detection, Estonian Wordnet integration and rule-based information extraction. Accompanied by a detailed API documentation and comprehensive tutorials, EstNLTK is suitable for a wide range of audience. We believe EstNLTK is mature enough to be used for developing NLP-backed systems both in industry and research. EstNLTK is freely available under the GNU GPL version 2+ license, which is standard for academic software.
South African National Centre for Digital Language Resources
Authors: Justus Roux
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Management

This presentation introduces the imminent establishment of a new language resource infrastructure focusing on languages spoken in Southern Africa, with an eventual aim to become a hub for digital language resources within Sub-Saharan Africa. The Constitution of South Africa makes provision for 11 official languages all with equal status. The current language Resource Management Agency will be merged with the new Centre, which will have a wider focus than that of data acquisition, management and distribution. The Centre will entertain two main programs: Digitisation and Digital Humanities. The digitisation program will focus on the systematic digitisation of relevant text, speech and multi-modal data across the official languages. Relevancy will be determined by a Scientific Advisory Board. This will take place on a continuous basis through specified projects allocated to national members of the Centre, as well as through open-calls aimed at the academic as well as local communities. The digital resources will be managed and distributed through a dedicated web-based portal. The development of the Digital Humanities program will entail extensive academic support for projects implementing digital language based data. The Centre will function as an enabling research infrastructure primarily supported by national government and hosted by the North-West University.
Design and Development of the MERLIN Learner Corpus Platform
Authors: Verena Lyding, Karin Sch{\"o}ne
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

In this paper, we report on the design and development of an online search platform for the MERLIN corpus of learner texts in Czech, German and Italian. It was created in the context of the MERLIN project, which aims at empirically illustrating features of the Common European Framework of Reference (CEFR) for evaluating language competences based on authentic learner text productions compiled into a learner corpus. Furthermore, the project aims at providing access to the corpus through a search interface adapted to the needs of multifaceted target groups involved with language learning and teaching. This article starts by providing a brief overview on the project ambition, the data resource and its intended target groups. Subsequently, the main focus of the article is on the design and development process of the platform, which is carried out in a user-centred fashion. The paper presents the user studies carried out to collect requirements, details the resulting decisions concerning the platform design and its implementation, and reports on the evaluation of the platform prototype and final adjustments.
FLAT: Constructing a CLARIN Compatible Home for Language Resources
Authors: Menzo Windhouwer, Marc Kemps-Snijders, Paul Trilsbeek, Andr{\'e} Moreira, Bas van der Veen, Guilherme Silva, Daniel von Reihn
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Management

Language resources are valuable assets, both for institutions and researchers. To safeguard these resources requirements for repository systems and data management have been specified by various branch organizations, e.g., CLARIN and the Data Seal of Approval. This paper describes these and some additional ones posed by the authors{'} home institutions. And it shows how they are met by FLAT, to provide a new home for language resources. The basis of FLAT is formed by the Fedora Commons repository system. This repository system can meet many of the requirements out-of-the box, but still additional configuration and some development work is needed to meet the remaining ones, e.g., to add support for Handles and Component Metadata. This paper describes design decisions taken in the construction of FLAT{'}s system architecture via a mix-and-match strategy, with a preference for the reuse of existing solutions. FLAT is developed and used by the Meertens Institute and The Language Archive, but is also freely available for anyone in need of a CLARIN-compliant repository for their language resources.
CLARIAH in the Netherlands
Authors: Jan Odijk
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

I introduce CLARIAH in the Netherlands, which aims to contribute the Netherlands part of a Europe-wide humanities research infrastructure. I describe the digital turn in the humanities, the background and context of CLARIAH, both nationally and internationally, its relation to the CLARIN and DARIAH infrastructures, and the rationale for joining forces between CLARIN and DARIAH in the Netherlands. I also describe the first results of joining forces as achieved in the CLARIAH-SEED project, and the plans of the CLARIAH-CORE project, which is currently running
Crosswalking from CMDI to Dublin Core and MARC 21
Authors: Claus Zinn, Thorsten Trippel, Steve Kaminski, Emanuel Dima
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

The Component MetaData Infrastructure (CMDI) is a framework for the creation and usage of metadata formats to describe all kinds of resources in the CLARIN world. To better connect to the library world, and to allow librarians to enter metadata for linguistic resources into their catalogues, a crosswalk from CMDI-based formats to bibliographic standards is required. The general and rather fluid nature of CMDI, however, makes it hard to map arbitrary CMDI schemas to metadata standards such as Dublin Core (DC) or MARC 21, which have a mature, well-defined and fixed set of field descriptors. In this paper, we address the issue and propose crosswalks between CMDI-based profiles originating from the NaLiDa project and DC and MARC 21, respectively.
Data Management Plans and Data Centers
Authors: Denise DiPersio, Christopher Cieri, Daniel Jaquette
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Management

Data management plans, data sharing plans and the like are now required by funders worldwide as part of research proposals. Concerned with promoting the notion of open scientific data, funders view such plans as the framework for satisfying the generally accepted requirements for data generated in funded research projects, among them that it be accessible, usable, standardized to the degree possible, secure and stable. This paper examines the origins of data management plans, their requirements and issues they raise for data centers and HLT resource development in general.
UIMA-Based JCoRe 2.0 Goes GitHub and Maven Central â€• State-of-the-Art Software Resource Engineering and Distribution of NLP Pipelines
Authors: Udo Hahn, Franz Matthies, Erik Faessler, Johannes Hellrich
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Articles, Management

We introduce JCoRe 2.0, the relaunch of a UIMA-based open software repository for full-scale natural language processing originating from the Jena University Language {\&} Information Engineering (JULIE) Lab. In an attempt to put the new release of JCoRe on firm software engineering ground, we uploaded it to GitHub, a social coding platform, with an underlying source code versioning system and various means to support collaboration for software development and code modification management. In order to automate the builds of complex NLP pipelines and properly represent and track dependencies of the underlying Java code, we incorporated Maven as part of our software configuration management efforts. In the meantime, we have deployed our artifacts on Maven Central, as well. JCoRe 2.0 offers a broad range of text analytics functionality (mostly) for English-language scientific abstracts and full-text articles, especially from the life sciences domain.
Facilitating Metadata Interoperability in CLARIN-DK
Authors: Lene Offersgaard, Dorte Haltrup Hansen
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

The issue for CLARIN archives at the metadata level is to facilitate the user{'}s possibility to describe their data, even with their own standard, and at the same time make these metadata meaningful for a variety of users with a variety of resource types, and ensure that the metadata are useful for search across all resources both at the national and at the European level. We see that different people from different research communities fill in the metadata in different ways even though the metadata was defined and documented. This has impacted when the metadata are harvested and displayed in different environments. A loss of information is at stake. In this paper we view the challenges of ensuring metadata interoperability through examples of propagation of metadata values from the CLARIN-DK archive to the VLO. We see that the CLARIN Community in many ways support interoperability, but argue that agreeing upon standards, making clear definitions of the semantics of the metadata and their content is inevitable for the interoperability to work successfully. The key points are clear and freely available definitions, accessible documentation and easily usable facilities and guidelines for the metadata creators.
The IPR-cleared Corpus of Contemporary Written and Spoken Romanian Language
Authors: Dan Tufi{\textcommabelow{s}}, Verginica Barbu Mititelu, Elena Irimia, {\textcommabelow{S}}tefan Daniel Dumitrescu, Tiberiu Boro{\textcommabelow{s}}
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Lemmatization, Part-Of-Speech Tagging

The article describes the current status of a large national project, CoRoLa, aiming at building a reference corpus for the contemporary Romanian language. Unlike many other national corpora, CoRoLa contains only - IPR cleared texts and speech data, obtained from some of the country{'}s most representative publishing houses, broadcasting agencies, editorial offices, newspapers and popular bloggers. For the written component 500 million tokens are targeted and for the oral one 300 hours of recordings. The choice of texts is done according to their functional style, domain and subdomain, also with an eye to the international practice. A metadata file (following the CMDI model) is associated to each text file. Collected texts are cleaned and transformed in a format compatible with the tools for automatic processing (segmentation, tokenization, lemmatization, part-of-speech tagging). The paper also presents up-to-date statistics about the structure of the corpus almost two years before its official launching. The corpus will be freely available for searching. Users will be able to download the results of their searches and those original files when not against stipulations in the protocols we have with text providers.
SYN2015: Representative Corpus of Contemporary Written Czech
Authors: Michal K{\v{r}}en, V{\'a}clav Cvr{\v{c}}ek, Tom{\'a}{\v{s}} {\v{C}}apka, Anna {\v{C}}erm{\'a}kov{\'a}, Milena Hn{\'a}tkov{\'a}, Lucie Chlumsk{\'a}, Tom{\'a}{\v{s}} Jel{\'\i}nek, Dominika Kov{\'a}{\v{r}}{\'\i}kov{\'a}, Vladim{\'\i}r Petkevi{\v{c}}, Pavel Proch{\'a}zka, Hana Skoumalov{\'a}, Michal {\v{S}}krabal, Petr Trune{\v{c}}ek, Pavel Vond{\v{r}}i{\v{c}}ka, Adrian Jan Zasina
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: text-classification, Text Classification

The paper concentrates on the design, composition and annotation of SYN2015, a new 100-million representative corpus of contemporary written Czech. SYN2015 is a sequel of the representative corpora of the SYN series that can be described as traditional (as opposed to the web-crawled corpora), featuring cleared copyright issues, well-defined composition, reliability of annotation and high-quality text processing. At the same time, SYN2015 is designed as a reflection of the variety of written Czech text production with necessary methodological and technological enhancements that include a detailed bibliographic annotation and text classification based on an updated scheme. The corpus has been produced using a completely rebuilt text processing toolchain called SynKorp. SYN2015 is lemmatized, morphologically and syntactically annotated with state-of-the-art tools. It has been published within the framework of the Czech National Corpus and it is available via the standard corpus query interface KonText at http://kontext.korpus.cz as well as a dataset in shuffled format.
LREC as a Graph: People and Resources in a Network
Authors: Riccardo Del Gratta, Francesca Frontini, Monica Monachini, Gabriella Pardelli, Irene Russo, Roberto Bartolini, Fahad Khan, Claudia Soria, Nicoletta Calzolari
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

This proposal describes a new way to visualise resources in the LREMap, a community-built repository of language resource descriptions and uses. The LREMap is represented as a force-directed graph, where resources, papers and authors are nodes. The analysis of the visual representation of the underlying graph is used to study how the community gathers around LRs and how LRs are used in research.
The Public License Selector: Making Open Licensing Easier
Authors: Pawel Kamocki, Pavel Stra{\v{n}}{\'a}k, Michal Sedl{\'a}k
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

Researchers in Natural Language Processing rely on availability of data and software, ideally under open licenses, but little is done to actively encourage it. In fact, the current Copyright framework grants exclusive rights to authors to copy their works, make them available to the public and make derivative works (such as annotated language corpora). Moreover, in the EU databases are protected against unauthorized extraction and re-utilization of their contents. Therefore, proper public licensing plays a crucial role in providing access to research data. A public license is a license that grants certain rights not to one particular user, but to the general public (everybody). Our article presents a tool that we developed and whose purpose is to assist the user in the licensing process. As software and data should be licensed under different licenses, the tool is composed of two separate parts: Data and Software. The underlying logic as well as elements of the graphic interface are presented below.
NLP Infrastructure for the Lithuanian Language
Authors: Daiva Vitkut{\.e}-Ad{\v{z}}gauskien{\.e}, Andrius Utka, Darius Amilevi{\v{c}}ius, Tomas Krilavi{\v{c}}ius
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Management, named-entity-recognition, Named Entity Recognition, Named Entity Recognition (NER), Sentiment Analysis

The Information System for Syntactic and Semantic Analysis of the Lithuanian language (lith. Lietuvi{\k{u}} kalbos sintaksin{\.e}s ir semantin{\.e}s analiz{\.e}s informacin{\.e} sistema, LKSSAIS) is the first infrastructure for the Lithuanian language combining Lithuanian language tools and resources for diverse linguistic research and applications tasks. It provides access to the basic as well as advanced natural language processing tools and resources, including tools for corpus creation and management, text preprocessing and annotation, ontology building, named entity recognition, morphosyntactic and semantic analysis, sentiment analysis, etc. It is an important platform for researchers and developers in the field of natural language technology.
CodE Alltag: A German-Language E-Mail Corpus
Authors: Ulrike Krieg-Holz, Christian Schuschnig, Franz Matthies, Benjamin Redling, Udo Hahn
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Descriptive

We introduce CODE ALLTAG, a text corpus composed of German-language e-mails. It is divided into two partitions: the first of these portions, CODE ALLTAG{\_}XL, consists of a bulk-size collection drawn from an openly accessible e-mail archive (roughly 1.5M e-mails), whereas the second portion, CODE ALLTAG{\_}S+d, is much smaller in size (less than thousand e-mails), yet excels with demographic data from each author of an e-mail. CODE ALLTAG, thus, currently constitutes the largest E-Mail corpus ever built. In this paper, we describe, for both parts, the solicitation process for gathering e-mails, present descriptive statistical properties of the corpus, and, for CODE ALLTAG{\_}S+d, reveal a compilation of demographic features of the donors of e-mails.
Rapid Development of Morphological Analyzers for Typologically Diverse Languages
Authors: Seth Kulick, Ann Bies
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Translation

The Low Resource Language research conducted under DARPA{'}s Broad Operational Language Translation (BOLT) program required the rapid creation of text corpora of typologically diverse languages (Turkish, Hausa, and Uzbek) which were annotated with morphological information, along with other types of annotation. Since the output of morphological analyzers is a significant aid to morphological annotation, we developed a morphological analyzer for each language in order to support the annotation task, and also as a deliverable by itself. Our framework for analyzer creation results in tables similar to those used in the successful SAMA analyzer for Arabic, but with a more abstract linguistic level, from which the tables are derived. A lexicon was developed from available resources for integration with the analyzer, and given the speed of development and uncertain coverage of the lexicon, we assumed that the analyzer would necessarily be lacking in some coverage for the project annotation. Our analyzer framework was therefore focused on rapid implementation of the key structures of the language, together with accepting {``}wildcard{''} solutions as possible analyses for a word with an unknown stem, building upon our similar experiences with morphological annotation with Modern Standard Arabic and Egyptian Arabic.
A Neural Lemmatizer for Bengali
Authors: Abhisek Chakrabarty, Akshay Chaturvedi, Utpal Garain
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: LEMMA, Lemmatization

We propose a novel neural lemmatization model which is language independent and supervised in nature. To handle the words in a neural framework, word embedding technique is used to represent words as vectors. The proposed lemmatizer makes use of contextual information of the surface word to be lemmatized. Given a word along with its contextual neighbours as input, the model is designed to produce the lemma of the concerned word as output. We introduce a new network architecture that permits only dimension specific connections between the input and the output layer of the model. For the present work, Bengali is taken as the reference language. Two datasets are prepared for training and testing purpose consisting of 19,159 and 2,126 instances respectively. As Bengali is a resource scarce language, these datasets would be beneficial for the respective research community. Evaluation method shows that the neural lemmatizer achieves 69.57{\%} accuracy on the test dataset and outperforms the simple cosine similarity based baseline strategy by a margin of 1.37{\%}.
A Finite-state Morphological Analyser for Tuvan
Authors: Francis Tyers, Aziyana Bayyr-ool, Aelita Salchak, Jonathan Washington
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

{\textasciitilde}This paper describes the development of free/open-source finite-state morphological transducers for Tuvan, a Turkic language spoken in and around the Tuvan Republic in Russia. The finite-state toolkit used for the work is the Helsinki Finite-State Toolkit (HFST), we use the lexc formalism for modelling the morphotactics and twol formalism for modelling morphophonological alternations. We present a novel description of the morphological combinatorics of pseudo-derivational morphemes in Tuvan. An evaluation is presented which shows that the transducer has a reasonable coverage―around 93{\%}―on freely-available corpora of the languages, and high precision―over 99{\%}―on a manually verified test set.
T\=ezaurs.lv: the Largest Open Lexical Database for Latvian
Authors: Andrejs Spektors, Ilze Auzina, Roberts Dargis, Normunds Gruzitis, Peteris Paikens, Lauma Pretkalnina, Laura Rituma, Baiba Saulite
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

We describe an extensive and versatile lexical resource for Latvian, an under-resourced Indo-European language, which we call Tezaurs (Latvian for {`}thesaurus{'}). It comprises a large explanatory dictionary of more than 250,000 entries that are derived from more than 280 external sources. The dictionary is enriched with phonetic, morphological, semantic and other annotations, as well as augmented by various language processing tools allowing for the generation of inflectional forms and pronunciation, for on-the-fly selection of corpus examples, for suggesting synonyms, etc. Tezaurs is available as a public and widely used web application for end-users, as an open data set for the use in language technology (LT), and as an API â€• a set of web services for the integration into third-party applications. The ultimate goal of Tezaurs is to be the central computational lexicon for Latvian, bringing together all Latvian words and frequently used multi-word units and allowing for the integration of other LT resources and tools.