pwc-archive/papers-with-abstracts huggingface dataset:
A Bilingual Discourse Corpus and Its Applications
Authors: Yang Liu, Jiajun Zhang, Cheng-qing Zong, Yating Yang, Xi Zhou
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Machine Translation, Translation

Existing discourse research only focuses on the monolingual languages and the inconsistency between languages limits the power of the discourse theory in multilingual applications such as machine translation. To address this issue, we design and build a bilingual discource corpus in which we are currently defining and annotating the bilingual elementary discourse units (BEDUs). The BEDUs are then organized into hierarchical structures. Using this discourse style, we have annotated nearly 20K LDC sentences. Finally, we design a bilingual discourse based method for machine translation evaluation and show the effectiveness of our bilingual discourse annotations.
Adding Semantic Relations to a Large-Coverage Connective Lexicon of German
Authors: Tatjana Scheffler, Manfred Stede
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

DiMLex is a lexicon of German connectives that can be used for various language understanding purposes. We enhanced the coverage to 275 connectives, which we regard as covering all known German discourse connectives in current use. In this paper, we consider the task of adding the semantic relations that can be expressed by each connective. After discussing different approaches to retrieving semantic information, we settle on annotating each connective with senses from the new PDTB 3.0 sense hierarchy. We describe our new implementation in the extended DiMLex, which will be available for research purposes.
Corpus Resources for Dispute Mediation Discourse
Authors: Mathilde Janier, Chris Reed
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

Dispute mediation is a growing activity in the resolution of conflicts, and more and more research emerge to enhance and better understand this (until recently) understudied practice. Corpus analyses are necessary to study discourse in this context; yet, little data is available, mainly because of its confidentiality principle. After proposing hints and avenues to acquire transcripts of mediation sessions, this paper presents the Dispute Mediation Corpus, which gathers annotated excerpts of mediation dialogues. Although developed as part of a project on argumentation, it is freely available and the text data can be used by anyone. This first-ever open corpus of mediation interactions can be of interest to scholars studying discourse, but also conflict resolution, argumentation, linguistics, communication, etc. We advocate for using and extending this resource that may be valuable to a large variety of domains of research, particularly those striving to enhance the study of the rapidly growing activity of dispute mediation.
A Tagged Corpus for Automatic Labeling of Disabilities in Medical Scientific Papers
Authors: Carlos Valmaseda, Juan Martinez-Romo, Lourdes Araujo
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

This paper presents the creation of a corpus of labeled disabilities in scientific papers. The identification of medical concepts in documents and, especially, the identification of disabilities, is a complex task mainly due to the variety of expressions that can make reference to the same problem. Currently there is not a set of documents manually annotated with disabilities with which to evaluate an automatic detection system of such concepts. This is the reason why this corpus arises, aiming to facilitate the evaluation of systems that implement an automatic annotation tool for extracting biomedical concepts such as disabilities. The result is a set of scientific papers manually annotated. For the selection of these scientific papers has been conducted a search using a list of rare diseases, since they generally have associated several disabilities of different kinds.
Fine-Grained Chinese Discourse Relation Labelling
Authors: Huan-Yuan Chen, Wan-Shan Liao, Hen-Hsen Huang, Hsin-Hsi Chen
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Relation

This paper explores several aspects together for a fine-grained Chinese discourse analysis. We deal with the issues of ambiguous discourse markers, ambiguous marker linkings, and more than one discourse marker. A universal feature representation is proposed. The pair-once postulation, cross-discourse-unit-first rule and word-pair-marker-first rule select a set of discourse markers from ambiguous linkings. Marker-Sum feature considers total contribution of markers and Marker-Preference feature captures the probability distribution of discourse functions of a representative marker by using preference rule. The HIT Chinese discourse relation treebank (HIT-CDTB) is used to evaluate the proposed models. The 25-way classifier achieves 0.57 micro-averaged F-score.
Annotating Discourse Relations in Spoken Language: A Comparison of the PDTB and CCR Frameworks
Authors: Ines Rehbein, Merel Scholman, Vera Demberg
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Relation

In discourse relation annotation, there is currently a variety of different frameworks being used, and most of them have been developed and employed mostly on written data. This raises a number of questions regarding interoperability of discourse relation annotation schemes, as well as regarding differences in discourse annotation for written vs. spoken domains. In this paper, we describe ouron annotating two spoken domains from the SPICE Ireland corpus (telephone conversations and broadcast interviews) according todifferent discourse annotation schemes, PDTB 3.0 and CCR. We show that annotations in the two schemes can largely be mappedone another, and discuss differences in operationalisations of discourse relation schemes which present a challenge to automatic mapping. We also observe systematic differences in the prevalence of implicit discourse relations in spoken data compared to written texts,find that there are also differences in the types of causal relations between the domains. Finally, we find that PDTB 3.0 addresses many shortcomings of PDTB 2.0 wrt. the annotation of spoken discourse, and suggest further extensions. The new corpus has roughly theof the CoNLL 2015 Shared Task test set, and we hence hope that it will be a valuable resource for the evaluation of automatic discourse relation labellers.
Enhancing The RATP-DECODA Corpus With Linguistic Annotations For Performing A Large Range Of NLP Tasks
Authors: Carole Lailler, L, Ana{\"\i}s eau, Fr{\'e}d{\'e}ric B{\'e}chet, Yannick Est{\`e}ve, Paul Del{\'e}glise
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Semantic Parsing

In this article, we present the RATP-DECODA Corpus which is composed by a set of 67 hours of speech from telephone conversations of a Customer Care Service (CCS). This corpus is already available on line at http://sldr.org/sldr000847/fr in its first version. However, many enhancements have been made in order to allow the development of automatic techniques to transcript conversations and to capture their meaning. These enhancements fall into two categories: firstly, we have increased the size of the corpus with manual transcriptions from a new operational day; secondly we have added new linguistic annotations to the whole corpus (either manually or through an automatic processing) in order to perform various linguistic tasks from syntactic and semantic parsing to dialog act tagging and dialog summarization.
Parallel Discourse Annotations on a Corpus of Short Texts
Authors: Manfred Stede, Stergos Afantenos, Andreas Peldszus, Nicholas Asher, J{\'e}r{\'e}my Perret
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

We present the first corpus of texts annotated with two alternative approaches to discourse structure, Rhetorical Structure Theory (Mann and Thompson, 1988) and Segmented Discourse Representation Theory (Asher and Lascarides, 2003). 112 short argumentative texts have been analyzed according to these two theories. Furthermore, in previous work, the same texts have already been annotated for their argumentation structure, according to the scheme of Peldszus and Stede (2013). This corpus therefore enables studies of correlations between the two accounts of discourse structure, and between discourse and argumentation. We converted the three annotation formats to a common dependency tree format that enables to compare the structures, and we describe some initial findings.
An Annotated Corpus of Direct Speech
Authors: John Lee, Chak Yan Yeung
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

We propose a scheme for annotating direct speech in literary texts, based on the Text Encoding Initiative (TEI) and the coreference annotation guidelines from the Message Understanding Conference (MUC). The scheme encodes the speakers and listeners of utterances in a text, as well as the quotative verbs that reports the utterances. We measure inter-annotator agreement on this annotation task. We then present statistics on a manually annotated corpus that consists of books from the New Testament. Finally, we visualize the corpus as a conversational network.
Evaluating the Noisy Channel Model for the Normalization of Historical Texts: Basque, Spanish and Slovene
Authors: Izaskun Etxeberria, I{\~n}aki Alegria, Larraitz Uria, Mans Hulden
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

This paper presents a method for the normalization of historical texts using a combination of weighted finite-state transducers and language models. We have extended our previous work on the normalization of dialectal texts and tested the method against a 17th century literary work in Basque. This preprocessed corpus is made available in the LREC repository. The performance of this method for learning relations between historical and contemporary word forms is evaluated against resources in three languages. The method we present learns to map phonological changes using a noisy channel model. The model is based on techniques commonly used for phonological inference and producing Grapheme-to-Grapheme conversion systems encoded as weighted transducers and produces F-scores above 80{\%} in the task for Basque. A wider evaluation shows that the approach performs equally well with all the languages in our evaluation suite: Basque, Spanish and Slovene. A comparison against other methods that address the same task is also provided.
Farasa: A New Fast and Accurate Arabic Word Segmenter
Authors: Kareem Darwish, Hamdy Mubarak
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: valid

In this paper, we present Farasa (meaning insight in Arabic), which is a fast and accurate Arabic segmenter. Segmentation involves breaking Arabic words into their constituent clitics. Our approach is based on SVMrank using linear kernels. The features that we utilized account for: likelihood of stems, prefixes, suffixes, and their combination; presence in lexicons containing valid stems and named entities; and underlying stem templates. Farasa outperforms or equalizes state-of-the-art Arabic segmenters, namely QATARA and MADAMIRA. Meanwhile, Farasa is nearly one order of magnitude faster than QATARA and two orders of magnitude faster than MADAMIRA. The segmenter should be able to process one billion words in less than 5 hours. Farasa is written entirely in native Java, with no external dependencies, and is open-source.
A Morphological Lexicon of Esperanto with Morpheme Frequencies
Authors: Eckhard Bick
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: POS

This paper discusses the internal structure of complex Esperanto words (CWs). Using a morphological analyzer, possible affixation and compounding is checked for over 50,000 Esperanto lexemes against a list of 17,000 root words. Morpheme boundaries in the resulting analyses were then checked manually, creating a CW dictionary of 28,000 words, representing 56.4{\%} of the lexicon, or 19.4{\%} of corpus tokens. The error percentage of the EspGram morphological analyzer for new corpus CWs was 4.3{\%} for types and 6.4{\%} for tokens, with a recall of almost 100{\%}, and wrong/spurious boundaries being more common than missing ones. For pedagogical purposes a morpheme frequency dictionary was constructed for a 16 million word corpus, confirming the importance of agglutinative derivational morphemes in the Esperanto lexicon. Finally, as a means to reduce the morphological ambiguity of CWs, we provide POS likelihoods for Esperanto suffixes.
How does Dictionary Size Influence Performance of Vietnamese Word Segmentation?
Authors: Wuying Liu, Lin Wang
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Segmentation, Vietnamese Word Segmentation

Vietnamese word segmentation (VWS) is a challenging basic issue for natural language processing. This paper addresses the problem of how does dictionary size influence VWS performance, proposes two novel measures: square overlap ratio (SOR) and relaxed square overlap ratio (RSOR), and validates their effectiveness. The SOR measure is the product of dictionary overlap ratio and corpus overlap ratio, and the RSOR measure is the relaxed version of SOR measure under an unsupervised condition. The two measures both indicate the suitable degree between segmentation dictionary and object corpus waiting for segmentation. The experimental results show that the more suitable, neither smaller nor larger, dictionary size is better to achieve the state-of-the-art performance for dictionary-based Vietnamese word segmenters.
Giving Lexical Resources a Second Life: D\'emonette, a Multi-sourced Morpho-semantic Network for French
Authors: Nabil Hathout, Fiammetta Namer
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Descriptive, Information Retrieval, Retrieval

D{\'e}monette is a derivational morphological network designed for the description of French. Its original architecture enables its use as a formal framework for the description of morphological analyses and as a repository for existing lexicons. It is fed with a variety of resources, which all are already validated. The harmonization of their content into a unified format provides them a second life, in which they are enriched with new properties, provided these are deductible from their contents. D{\'e}monette is released under a Creative Commons license. It is usable for theoretical and descriptive research in morphology, as a source of experimental material for psycholinguistics, natural language processing (NLP) and information retrieval (IR), where it fills a gap, since French lacks a large-coverage derivational resources database. The article presents the integration of two existing lexicons into D{\'e}monette. The first is Verbaction, a lexicon of deverbal action nouns. The second is Lexeur, a database of agent nouns in -eur derived from verbs or from nouns.
Syntactic Analysis of Phrasal Compounds in Corpora: a Challenge for NLP Tools
Authors: Carola Trips
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

The paper introduces a {``}train once, use many{''} approach for the syntactic analysis of phrasal compounds (PC) of the type XP+N like {``}Would you like to sit on my knee?{''} nonsense. PCs are a challenge for NLP tools since they require the identification of a syntactic phrase within a morphological complex. We propose a method which uses a state-of-the-art dependency parser not only to analyse sentences (the environment of PCs) but also to compound the non-head of PCs in a well-defined particular condition which is the analysis of the non-head spanning from the left boundary (mostly marked by a determiner) to the nominal head of the PC. This method contains the following steps: (a) the use an English state-of-the-art dependency parser with data comprising sentences with PCs from the British National Corpus (BNC), (b) the detection of parsing errors of PCs, (c) the separate treatment of the non-head structure using the same model, and (d) the attachment of the non-head to the compound head. The evaluation of the method showed that the accuracy of 76{\%} could be improved by adding a step in the PC compounder module which specified user-defined contexts being sensitive to the part of speech of the non-head parts and by using TreeTagger, in line with our approach.
DALILA: The Dialectal Arabic Linguistic Learning Assistant
Authors: Salam Khalifa, Houda Bouamor, Nizar Habash
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

Dialectal Arabic (DA) poses serious challenges for Natural Language Processing (NLP). The number and sophistication of tools and datasets in DA are very limited in comparison to Modern Standard Arabic (MSA) and other languages. MSA tools do not effectively model DA which makes the direct use of MSA NLP tools for handling dialects impractical. This is particularly a challenge for the creation of tools to support learning Arabic as a living language on the web, where authentic material can be found in both MSA and DA. In this paper, we present the Dialectal Arabic Linguistic Learning Assistant (DALILA), a Chrome extension that utilizes cutting-edge Arabic dialect NLP research to assist learners and non-native speakers in understanding text written in either MSA or DA. DALILA provides dialectal word analysis and English gloss corresponding to each word.
Refurbishing a Morphological Database for German
Authors: Petra Steiner
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

The CELEX database is one of the standard lexical resources for German. It yields a wealth of data especially for phonological and morphological applications. The morphological part comprises deep-structure morphological analyses of German. However, as it was developed in the Nineties, both encoding and spelling are outdated. About one fifth of over 50,000 datasets contain umlauts and signs such as {\ss}. Changes to a modern version cannot be obtained by simple substitution. In this paper, we shortly describe the original content and form of the orthographic and morphological database for German in CELEX. Then we present our work on modernizing the linguistic data. Lemmas and morphological analyses are transferred to a modern standard of encoding by first merging orthographic and morphological information of the lemmas and their entries and then performing a second substitution for the morphs within their morphological analyses. Changes to modern German spelling are performed by substitution rules according to orthographical standards. We show an example of the use of the data for the disambiguation of morphological structures. The discussion describes prospects of future work on this or similar lexicons. The Perl script is publicly available on our website.
Encoding Adjective Scales for Fine-grained Resources
Authors: C{\'e}dric Lopez, Fr{\'e}d{\'e}rique Segond, Christiane Fellbaum
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Attribute

We propose an automatic approach towards determining the relative location of adjectives on a common scale based on their strength. We focus on adjectives expressing different degrees of goodness occurring in French product (perfumes) reviews. Using morphosyntactic patterns, we extract from the reviews short phrases consisting of a noun that encodes a particular aspect of the perfume and an adjective modifying that noun. We then associate each such n-gram with the corresponding product aspect and its related star rating. Next, based on the star scores, we generate adjective scales reflecting the relative strength of specific adjectives associated with a shared attribute of the product. An automatic ordering of the adjectives {``}correct{''} (correct), {``}sympa{''} (nice), {``}bon{''} (good) and {``}excellent{''} (excellent) according to their score in our resource is consistent with an intuitive scale based on human judgments. Our long-term objective is to generate different adjective scales in an empirical manner, which could allow the enrichment of lexical resources.
SCARE â€• The Sentiment Corpus of App Reviews with Fine-grained Annotations in German
Authors: Mario S{\"a}nger, Ulf Leser, Steffen Kemmerer, Peter Adolphs, Roman Klinger
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Sentiment Analysis

The automatic analysis of texts containing opinions of users about, e.g., products or political views has gained attention within the last decades. However, previous work on the task of analyzing user reviews about mobile applications in app stores is limited. Publicly available corpora do not exist, such that a comparison of different methods and models is difficult. We fill this gap by contributing the Sentiment Corpus of App Reviews (SCARE), which contains fine-grained annotations of application aspects, subjective (evaluative) phrases and relations between both. This corpus consists of 1,760 annotated application reviews from the Google Play Store with 2,487 aspects and 3,959 subjective phrases. We describe the process and methodology how the corpus was created. The Fleiss Kappa between four annotators reveals an agreement of 0.72. We provide a strong baseline with a linear-chain conditional random field and word-embedding features with a performance of 0.62 for aspect detection and 0.63 for the extraction of subjective phrases. The corpus is available to the research community to support the development of sentiment analysis methods on mobile application reviews.
Datasets for Aspect-Based Sentiment Analysis in French
Authors: Marianna Apidianaki, Xavier Tannier, C{\'e}cile Richart
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Aspect-Based Sentiment Analysis, Aspect-Based Sentiment Analysis (ABSA), Sentiment Analysis

Aspect Based Sentiment Analysis (ABSA) is the task of mining and summarizing opinions from text about specific entities and their aspects. This article describes two datasets for the development and testing of ABSA systems for French which comprise user reviews annotated with relevant entities, aspects and polarity values. The first dataset contains 457 restaurant reviews (2365 sentences) for training and testing ABSA systems, while the second contains 162 museum reviews (655 sentences) dedicated to out-of-domain evaluation. Both datasets were built as part of SemEval-2016 Task 5 {``}Aspect-Based Sentiment Analysis{''} where seven different languages were represented, and are publicly available for research purposes.
ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages
Authors: Samira Shaikh, Kit Cho, Tomek Strzalkowski, Laurie Feldman, John Lien, Ting Liu, George Aaron Broadwell
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

In this article we describe our method of automatically expanding an existing lexicon of words with affective valence scores. The automatic expansion process was done in English. In addition, we describe our procedure for automatically creating lexicons in languages where such resources may not previously exist. The foreign languages we discuss in this paper are Spanish, Russian and Farsi. We also describe the procedures to systematically validate our newly created resources. The main contributions of this work are: 1) A general method for expansion and creation of lexicons with scores of words on psychological constructs such as valence, arousal or dominance; and 2) a procedure for ensuring validity of the newly constructed resources.