pwc-archive/papers-with-abstracts huggingface dataset:
WAT-SL: A Customizable Web Annotation Tool for Segment Labeling
Authors: Johannes Kiesel, Henning Wachsmuth, Khalid Al-Khatib, Benno Stein
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4

A frequent type of annotations in text corpora are labeled text segments. General-purpose annotation tools tend to be overly comprehensive, often making the annotation process slower and more error-prone. We present WAT-SL, a new web-based tool that is dedicated to segment labeling and highly customizable to the labeling task at hand. We outline its main features and exemplify how we used it for a crowdsourced corpus with labeled argument units.
TextImager as a Generic Interface to R
Authors: Tolga Uslu, Wahed Hemati, Alex Mehler, er, Daniel Baumartz
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4

R is a very powerful framework for statistical modeling. Thus, it is of high importance to integrate R with state-of-the-art tools in NLP. In this paper, we present the functionality and architecture of such an integration by means of TextImager. We use the OpenCPU API to integrate R based on our own R-Server. This allows for communicating with R-packages and combining them with TextImager{'}s NLP-components.
GraWiTas: a Grammar-based Wikipedia Talk Page Parser
Authors: Benjamin Cabrera, Laura Steinert, Bj{\"o}rn Ross
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4

Wikipedia offers researchers unique insights into the collaboration and communication patterns of a large self-regulating community of editors. The main medium of direct communication between editors of an article is the article{'}s talk page. However, a talk page file is unstructured and therefore difficult to analyse automatically. A few parsers exist that enable its transformation into a structured data format. However, they are rarely open source, support only a limited subset of the talk page syntax {--} resulting in the loss of content {--} and usually support only one export format. Together with this article we offer a very fast, lightweight, open source parser with support for various output formats. In a preliminary evaluation it achieved a high accuracy. The parser uses a grammar-based approach {--} offering a transparent implementation and easy extensibility.
TWINE: A real-time system for TWeet analysis via INformation Extraction
Authors: Debora Nozza, Fausto Ristagno, Matteo Palmonari, Elisabetta Fersini, Manch, Pikakshi a, Enza Messina
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: geo-localization, named-entity-recognition, Named Entity Recognition, Named Entity Recognition (NER)

In the recent years, the amount of user generated contents shared on the Web has significantly increased, especially in social media environment, e.g. Twitter, Facebook, Google+. This large quantity of data has generated the need of reactive and sophisticated systems for capturing and understanding the underlying information enclosed in them. In this paper we present TWINE, a real-time system for the big data analysis and exploration of information extracted from Twitter streams. The proposed system based on a Named Entity Recognition and Linking pipeline and a multi-dimensional spatial geo-localization is managed by a scalable and flexible architecture for an interactive visualization of micropost streams insights. The demo is available at \url{http://twine-mind.cloudapp.net/streaming}.
Alto: Rapid Prototyping for Parsing and Translation
Authors: Johannes Gontrum, Jonas Groschwitz, Alex Koller, er, Christoph Teichmann
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Machine Translation, Semantic Parsing, Translation

We present Alto, a rapid prototyping tool for new grammar formalisms. Alto implements generic but efficient algorithms for parsing, translation, and training for a range of monolingual and synchronous grammar formalisms. It can easily be extended to new formalisms, which makes all of these algorithms immediately available for the new formalism.
CASSANDRA: A multipurpose configurable voice-enabled human-computer-interface
Authors: Tiberiu Boros, Stefan Daniel Dumitrescu, Sonia Pipa
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Natural Language Understanding, Question Answering, speech-recognition, Speech Recognition, Speech Synthesis, text-to-speech, Text to Speech, Text-To-Speech Synthesis

Voice enabled human computer interfaces (HCI) that integrate automatic speech recognition, text-to-speech synthesis and natural language understanding have become a commodity, introduced by the immersion of smart phones and other gadgets in our daily lives. Smart assistants are able to respond to simple queries (similar to text-based question-answering systems), perform simple tasks (call a number, reject a call etc.) and help organizing appointments. With this paper we introduce a newly created process automation platform that enables the user to control applications and home appliances and to query the system for information using a natural voice interface. We offer an overview of the technologies that enabled us to construct our system and we present different usage scenarios in home and office environments.
An Extensible Framework for Verification of Numerical Claims
Authors: James Thorne, Andreas Vlachos
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Fact Checking, Rumour Detection, Semantic Parsing

In this paper we present our automated fact checking system demonstration which we developed in order to participate in the Fast and Furious Fact Check challenge. We focused on simple numerical claims such as {``}population of Germany in 2015 was 80 million{''} which comprised a quarter of the test instances in the challenge, achieving 68{\%} accuracy. Our system extends previous work on semantic parsing and claim identification to handle temporal expressions and knowledge bases consisting of multiple tables, while relying solely on automatically generated training data. We demonstrate the extensible nature of our system by evaluating it on relations used in previous work. We make our system publicly available so that it can be used and extended by the community.
ADoCS: Automatic Designer of Conference Schedules
Authors: Diego Fern Vallejo Huanga, o, Paulina Adriana Morillo Alc{\'\i}var, C{\`e}sar Ferri Ram{\'\i}rez
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Articles, Clustering, Information Retrieval

Distributing papers into sessions in scientific conferences is a task consisting in grouping papers with common topics and considering the size restrictions imposed by the conference schedule. This problem can be seen as a semi-supervised clustering of scientific papers based on their features. This paper presents a web tool called ADoCS that solves the problem of configuring conference schedules by an automatic clustering of articles by similarity using a new algorithm considering size constraints.
A Web Interface for Diachronic Semantic Search in Spanish
Authors: Pablo Gamallo, Iv{\'a}n Rodr{\'\i}guez-Torres, Marcos Garcia
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4

This article describes a semantic system which is based on distributional models obtained from a chronologically structured language resource, namely Google Books Syntactic Ngrams.The models were created using dependency-based contexts and a strategy for reducing the vector space, which consists in selecting the more informative and relevant word contexts. The system allowslinguists to analize meaning change of Spanish words in the written language across time.
Multilingual CALL Framework for Automatic Language Exercise Generation from Free Text
Authors: Naiara Perez, Montse Cuadros
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Multiple-choice, Word Sense Disambiguation

This paper describes a web-based application to design and answer exercises for language learning. It is available in Basque, Spanish, English, and French. Based on open-source Natural Language Processing (NLP) technology such as word embedding models and word sense disambiguation, the application enables users to automatic create easily and in real time three types of exercises, namely, Fill-in-the-Gaps, Multiple Choice, and Shuffled Sentences questionnaires. These are generated from texts of the users{'} own choice, so they can train their language skills with content of their particular interest.
Audience Segmentation in Social Media
Authors: Verena Henrich, Alex Lang, er
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Segmentation, Sentiment Analysis

Understanding the social media audience is becoming increasingly important for social media analysis. This paper presents an approach that detects various audience attributes, including author location, demographics, behavior and interests. It works both for a variety of social media sources and for multiple languages. The approach has been implemented within IBM Watson Analytics for Social Media and creates author profiles for more than 300 different analysis domains every day.
The arText prototype: An automatic system for writing specialized texts
Authors: Iria da Cunha, M. Amor Montan{\'e}, Luis Hysa
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4

This article describes an automatic system for writing specialized texts in Spanish. The arText prototype is a free online text editor that includes different types of linguistic information. It is designed for a variety of end users and domains, including specialists and university students working in the fields of medicine and tourism, and laypersons writing to the public administration. ArText provides guidance on how to structure a text, prompts users to include all necessary contents in each section, and detects lexical and discourse problems in the text.
QCRI Live Speech Translation System
Authors: Fahim Dalvi, Yifan Zhang, Sameer Khurana, Nadir Durrani, Hassan Sajjad, Ahmed Abdelali, Hamdy Mubarak, Ahmed Ali, Stephan Vogel
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Machine Translation, Speech Recognition, Translation

This paper presents QCRI{'}s Arabic-to-English live speech translation system. It features modern web technologies to capture live audio, and broadcasts Arabic transcriptions and English translations simultaneously. Our Kaldi-based ASR system uses the Time Delay Neural Network (TDNN) architecture, while our Machine Translation (MT) system uses both phrase-based and neural frameworks. Although our neural MT system is slower than the phrase-based system, it produces significantly better translations and is memory efficient. The demo is available at \url{https://st.qcri.org/demos/livetranslation}.
A tool for extracting sense-disambiguated example sentences through user feedback
Authors: Beto Boullosa, Richard Eckart de Castilho, Alex Geyken, er, Lothar Lemnitzer, Iryna Gurevych
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Clustering, General Classification

This paper describes an application system aimed to help lexicographers in the extraction of example sentences for a given headword based on its different senses. The tool uses classification and clustering methods and incorporates user feedback to refine its results.
Lingmotif: Sentiment Analysis for the Digital Humanities
Authors: Antonio Moreno-Ortiz
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Sentiment Analysis

Lingmotif is a lexicon-based, linguistically-motivated, user-friendly, GUI-enabled, multi-platform, Sentiment Analysis desktop application. Lingmotif can perform SA on any type of input texts, regardless of their length and topic. The analysis is based on the identification of sentiment-laden words and phrases contained in the application{'}s rich core lexicons, and employs context rules to account for sentiment shifters. It offers easy-to-interpret visual representations of quantitative data (text polarity, sentiment intensity, sentiment profile), as well as a detailed, qualitative analysis of the text in terms of its sentiment. Lingmotif can also take user-provided plugin lexicons in order to account for domain-specific sentiment expression. Lingmotif currently analyzes English and Spanish texts.
RAMBLE ON: Tracing Movements of Popular Historical Figures
Authors: Stefano Menini, Rachele Sprugnoli, Giovanni Moretti, Enrico Bignotti, Sara Tonelli, Bruno Lepri
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4

We present RAMBLE ON, an application integrating a pipeline for frame-based information extraction and an interface to track and display movement trajectories. The code of the extraction pipeline and a navigator are freely available; moreover we display in a demonstrator the outcome of a case study carried out on trajectories of notable persons of the XX Century.
Autobank: a semi-automatic annotation tool for developing deep Minimalist Grammar treebanks
Authors: John Torr
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Machine Translation

This paper presents Autobank, a prototype tool for constructing a wide-coverage Minimalist Grammar (MG) (Stabler 1997), and semi-automatically converting the Penn Treebank (PTB) into a deep Minimalist treebank. The front end of the tool is a graphical user interface which facilitates the rapid development of a seed set of MG trees via manual reannotation of PTB preterminals with MG lexical categories. The system then extracts various dependency mappings between the source and target trees, and uses these in concert with a non-statistical MG parser to automatically reannotate the rest of the corpus. Autobank thus enables deep treebank conversions (and subsequent modifications) without the need for complex transduction algorithms accompanied by cascades of ad hoc rules; instead, the locus of human effort falls directly on the task of grammar construction itself.
Chatbot with a Discourse Structure-Driven Dialogue Management
Authors: Boris Galitsky, Dmitry Ilvovsky
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Chatbot, Dialogue Management, Management, Product Recommendation

We build a chat bot with iterative content exploration that leads a user through a personalized knowledge acquisition session. The chat bot is designed as an automated customer support or product recommendation agent assisting a user in learning product features, product usability, suitability, troubleshooting and other related tasks. To control the user navigation through content, we extend the notion of a linguistic discourse tree (DT) towards a set of documents with multiple sections covering a topic. For a given paragraph, a DT is built by DT parsers. We then combine DTs for the paragraphs of documents to form what we call extended DT, which is a basis for interactive content exploration facilitated by the chat bot. To provide cohesive answers, we use a measure of rhetoric agreement between a question and an answer by tree kernel learning of their DTs.
Marine Variable Linker: Exploring Relations between Changing Variables in Marine Science Literature
Authors: Erwin Marsi, Pinar Pinar {\O}zturk, Murat V. Ardelan
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4

We report on a demonstration system for text mining of literature in marine science and related disciplines. It automatically extracts variables ({``}CO2{''}) involved in events of change/increase/decrease ({``}increasing CO2{''}), as well as co-occurrence and causal relations among these events ({``}increasing CO2 causes a decrease in pH in seawater{''}), resulting in a big knowledge graph. A web-based graphical user interface targeted at marine scientists facilitates searching, browsing and visualising events and their relations in an interactive way.
Neoveille, a Web Platform for Neologism Tracking
Authors: Emmanuel Cartier
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Retrieval

This paper details a software designed to track neologisms in seven languages through newspapers monitor corpora. The platform combines state-of-the-art processes to track linguistic changes and a web platform for linguists to create and manage their corpora, accept or reject automatically identified neologisms, describe linguistically the accepted neologisms and follow their lifecycle on the monitor corpora. In the following, after a short state-of-the-art in Neologism Retrieval, Analysis and Life-tracking, we describe the overall architecture of the system. The platform can be freely browsed at \url{www.neoveille.org} where detailed presentation is given. Access to the editing modules is available upon request.
Building Web-Interfaces for Vector Semantic Models with the WebVectors Toolkit
Authors: Andrey Kutuzov, Elizaveta Kuzmenko
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Machine Translation, Named Entity Recognition (NER), Sentiment Analysis, Word Embeddings

In this demo we present WebVectors, a free and open-source toolkit helping to deploy web services which demonstrate and visualize distributional semantic models (widely known as word embeddings). WebVectors can be useful in a very common situation when one has trained a distributional semantics model for one{'}s particular corpus or language (tools for this are now widespread and simple to use), but then there is a need to demonstrate the results to general public over the Web. We show its abilities on the example of the living web services featuring distributional models for English, Norwegian and Russian.
InToEventS: An Interactive Toolkit for Discovering and Building Event Schemas
Authors: Germ{\'a}n Ferrero, Audi Primadhanty, Ariadna Quattoni
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Clustering, Slot Filling

Event Schema Induction is the task of learning a representation of events (e.g., bombing) and the roles involved in them (e.g, victim and perpetrator). This paper presents InToEventS, an interactive tool for learning these schemas. InToEventS allows users to explore a corpus and discover which kind of events are present. We show how users can create useful event schemas using two interactive clustering steps.
ICE: Idiom and Collocation Extractor for Research and Education
Authors: Vasanthi Vuppuluri, Shahryar Baki, An Nguyen, Rakesh Verma
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: POS, Question Answering

Collocation and idiom extraction are well-known challenges with many potential applications in Natural Language Processing (NLP). Our experimental, open-source software system, called ICE, is a python package for flexibly extracting collocations and idioms, currently in English. It also has a competitive POS tagger that can be used alone or as part of collocation/idiom extraction. ICE is available free of cost for research and educational uses in two user-friendly formats. This paper gives an overview of ICE and its performance, and briefly describes the research underlying the extraction algorithms.
Bib2vec: Embedding-based Search System for Bibliographic Information
Authors: Takuma Yoneda, Koki Mori, Makoto Miwa, Yutaka Sasaki
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Network Embedding, Topic Models

We propose a novel embedding model that represents relationships among several elements in bibliographic information with high representation ability and flexibility. Based on this model, we present a novel search system that shows the relationships among the elements in the ACL Anthology Reference Corpus. The evaluation results show that our model can achieve a high prediction ability and produce reasonable search results.
The SUMMA Platform Prototype
Authors: Renars Liepins, Ulrich Germann, Guntis Barzdins, Alex Birch, ra, Steve Renals, Susanne Weber, Peggy van der Kreeft, Herv{\'e} Bourlard, Jo{\~a}o Prieto, Ond{\v{r}}ej Klejch, Peter Bell, Alex Lazaridis, ros, Alfonso Mendes, Sebastian Riedel, Mariana S. C. Almeida, Pedro Balage, Shay B. Cohen, Tomasz Dwojak, Philip N. Garner, Andreas Giefer, Marcin Junczys-Dowmunt, Hina Imran, David Nogueira, Ahmed Ali, Mir, Sebasti{\~a}o a, Andrei Popescu-Belis, Lesly Miculicich Werlen, Nikos Papasarantopoulos, Abiola Obamuyide, Clive Jones, Fahim Dalvi, Andreas Vlachos, Yang Wang, Sibo Tong, Rico Sennrich, Nikolaos Pappas, Shashi Narayan, Marco Damonte, Nadir Durrani, Sameer Khurana, Ahmed Abdelali, Hassan Sajjad, Stephan Vogel, David Sheppey, Chris Hernon, Jeff Mitchell
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), General Classification, Machine Translation, Semantic Parsing, speech-recognition, Speech Recognition, Translation

We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadcast media, machine translation, automated tagging and classification of named entities, semantic parsing to detect relationships between entities, and automatic construction / augmentation of factual knowledge bases. Implemented on the Docker platform, it can easily be deployed, customised, and scaled to large volumes of incoming media streams.
Pragmatic descriptions of perceptual stimuli
Authors: Emiel van Miltenburg
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Image Description, Object Recognition

This research proposal discusses pragmatic factors in image description, arguing that current automatic image description systems do not take these factors into account. I present a general model of the human image description process, and propose to study this process using corpus analysis, experiments, and computational modeling. This will lead to a better characterization of human image description behavior, providing a road map for future research in automatic image description, and the automatic description of perceptual stimuli in general.
Detecting spelling variants in non-standard texts
Authors: Fabian Barteld
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4

Spelling variation in non-standard language, e.g. computer-mediated communication and historical texts, is usually treated as a deviation from a standard spelling, e.g. 2mr as an non-standard spelling for tomorrow. Consequently, in normalization {--} the standard approach of dealing with spelling variation {--} so-called non-standard words are mapped to their corresponding standard words. However, there is not always a corresponding standard word. This can be the case for single types (like emoticons in computer-mediated communication) or a complete language, e.g. texts from historical languages that did not develop to a standard variety. The approach presented in this thesis proposal deals with spelling variation in absence of reference to a standard. The task is to detect pairs of types that are variants of the same morphological word. An approach for spelling-variant detection is presented, where pairs of potential spelling variants are generated with Levenshtein distance and subsequently filtered by supervised machine learning. The approach is evaluated on historical Low German texts. Finally, further perspectives are discussed.
Discourse Relations and Conjoined VPs: Automated Sense Recognition
Authors: Valentina Pyatkin, Bonnie Webber
Date: 2017-04-01 00:00:00
Proceeding: EACL 2017 4
Tasks: Classification, Discourse Parsing, General Classification, Multi-Label Classification

Sense classification of discourse relations is a sub-task of shallow discourse parsing. Discourse relations can occur both across sentences (\textit{inter-sentential}) and within sentences (\textit{intra-sentential}), and more than one discourse relation can hold between the same units. Using a newly available corpus of discourse-annotated intra-sentential conjoined verb phrases, we demonstrate a sequential classification pipeline for their multi-label sense classification. We assess the importance of each feature used in the classification, the feature scope, and what is lost in moving from gold standard manual parses to the output of an off-the-shelf parser.