pwc-archive/papers-with-abstracts huggingface dataset:
MWEs in Treebanks: From Survey to Guidelines
Authors: Victoria Ros{\'e}n, Koenraad De Smedt, Gyri Sm{\o}rdal Losnegaard, Eduard Bej{\v{c}}ek, Agata Savary, Petya Osenova
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Survey

By means of an online survey, we have investigated ways in which various types of multiword expressions are annotated in existing treebanks. The results indicate that there is considerable variation in treatments across treebanks and thereby also, to some extent, across languages and across theoretical frameworks. The comparison is focused on the annotation of light verb constructions and verbal idioms. The survey shows that the light verb constructions either get special annotations as such, or are treated as ordinary verbs, while VP idioms are handled through different strategies. Based on insights from our investigation, we propose some general guidelines for annotating multiword expressions in treebanks. The recommendations address the following application-based needs: distinguishing MWEs from similar but compositional constructions; searching distinct types of MWEs in treebanks; awareness of literal and nonliteral meanings; and normalization of the MWE representation. The cross-lingually and cross-theoretically focused survey is intended as an aid to accessing treebanks and an aid for further work on treebank annotation.
Multiword Expressions Dataset for Indian Languages
Authors: Dhirendra Singh, Sudha Bhingardive, Pushpak Bhattacharyya
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Diversity, POS, TAG, valid

Multiword Expressions (MWEs) are used frequently in natural languages, but understanding the diversity in MWEs is one of the open problem in the area of Natural Language Processing. In the context of Indian languages, MWEs play an important role. In this paper, we present MWEs annotation dataset created for Indian languages viz., Hindi and Marathi. We extract possible MWE candidates using two repositories: 1) the POS-tagged corpus and 2) the IndoWordNet synsets. Annotation is done for two types of MWEs: compound nouns and light verb constructions. In the process of annotation, human annotators tag valid MWEs from these candidates based on the standard guidelines provided to them. We obtained 3178 compound nouns and 2556 light verb constructions in Hindi and 1003 compound nouns and 2416 light verb constructions in Marathi using two repositories mentioned before. This created resource is made available publicly and can be used as a gold standard for Hindi and Marathi MWE systems.
MarsaGram: an excursion in the forests of parsing trees
Authors: Philippe Blache, St{\'e}phane Rauzy, Gr{\'e}goire Montcheuil
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: General Classification

The question of how to compare languages and more generally the domain of linguistic typology, relies on the study of different linguistic properties or phenomena. Classically, such a comparison is done semi-manually, for example by extracting information from databases such as the WALS. However, it remains difficult to identify precisely regular parameters, available for different languages, that can be used as a basis towards modeling. We propose in this paper, focusing on the question of syntactic typology, a method for automatically extracting such parameters from treebanks, bringing them into a typology perspective. We present the method and the tools for inferring such information and navigating through the treebanks. The approach has been applied to 10 languages of the Universal Dependencies Treebank. We approach is evaluated by showing how automatic classification correlates with language families.
EasyTree: A Graphical Tool for Dependency Tree Annotation
Authors: Alexa Little, Stephen Tratz
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Data Visualization, Translation

This paper introduces EasyTree, a dynamic graphical tool for dependency tree annotation. Built in JavaScript using the popular D3 data visualization library, EasyTree allows annotators to construct and label trees entirely by manipulating graphics, and then export the corresponding data in JSON format. Human users are thus able to annotate in an intuitive way without compromising the machine-compatibility of the output. EasyTree has a number of features to assist annotators, including color-coded part-of-speech indicators and optional translation displays. It can also be customized to suit a wide range of projects; part-of-speech categories, edge labels, and many other settings can be edited from within the GUI. The system also utilizes UTF-8 encoding and properly handles both left-to-right and right-to-left scripts. By providing a user-friendly annotation tool, we aim to reduce time spent transforming data or learning to use the software, to improve the user experience for annotators, and to make annotation approachable even for inexperienced users. Unlike existing solutions, EasyTree is built entirely with standard web technologies{--}JavaScript, HTML, and CSS{--}making it ideal for web-based annotation efforts, including crowdsourcing efforts.
Hypergraph Modelization of a Syntactically Annotated English Wikipedia Dump
Authors: Edmundo Pavel Soriano Morales, Julien Ah-Pine, Sabine Loudcher
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Dependency Parsing, POS

Wikipedia, the well known internet encyclopedia, is nowadays a widely used source of information. To leverage its rich information, already parsed versions of Wikipedia have been proposed. We present an annotated dump of the English Wikipedia. This dump draws upon previously released Wikipedia parsed dumps. Still, we head in a different direction. In this parse we focus more into the syntactical characteristics of words: aside from the classical Part-of-Speech (PoS) tags and dependency parsing relations, we provide the full constituent parse branch for each word in a succinct way. Additionally, we propose a hypergraph network representation of the extracted linguistic information. The proposed modelization aims to take advantage of the information stocked within our parsed Wikipedia dump. We hope that by releasing these resources, researchers from the concerned communities will have a ready-to-experiment Wikipedia corpus to compare and distribute their work. We render public our parsed Wikipedia dump as well as the tool (and its source code) used to perform the parse. The hypergraph network and its related metadata is also distributed.
Detecting Annotation Scheme Variation in Out-of-Domain Treebanks
Authors: Yannick Versley, Julius Steen
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

To ensure portability of NLP systems across multiple domains, existing treebanks are often extended by adding trees from interesting domains that were not part of the initial annotation effort. In this paper, we will argue that it is both useful from an application viewpoint and enlightening from a linguistic viewpoint to detect and reduce divergence in annotation schemes between extant and new parts in a set of treebanks that is to be used in evaluation experiments. The results of our correction and harmonization efforts will be made available to the public as a test suite for the evaluation of constituent parsing.
Universal Dependencies for Persian
Authors: Mojgan Seraji, Filip Ginter, Joakim Nivre
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Sentence, valid

The Persian Universal Dependency Treebank (Persian UD) is a recent effort of treebanking Persian with Universal Dependencies (UD), an ongoing project that designs unified and cross-linguistically valid grammatical representations including part-of-speech tags, morphological features, and dependency relations. The Persian UD is the converted version of the Uppsala Persian Dependency Treebank (UPDT) to the universal dependencies framework and consists of nearly 6,000 sentences and 152,871 word tokens with an average sentence length of 25 words. In addition to the universal dependencies syntactic annotation guidelines, the two treebanks differ in tokenization. All words containing unsegmented clitics (pronominal and copula clitics) annotated with complex labels in the UPDT have been separated from the clitics and appear with distinct labels in the Persian UD. The treebank has its original syntactic annotation scheme based on Stanford Typed Dependencies. In this paper, we present the approaches taken in the development of the Persian UD.
Hard Time Parsing Questions: Building a QuestionBank for French
Authors: Djam{\'e} Seddah, C, Marie ito
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

We present the French Question Bank, a treebank of 2600 questions. We show that classical parsing model performance drop while the inclusion of this data set is highly beneficial without harming the parsing of non-question data. when facing out-of- domain data with strong structural diver- gences. Two thirds being aligned with the QB (Judge et al., 2006) and being freely available, this treebank will prove useful to build robust NLP systems.
Enhanced English Universal Dependencies: An Improved Representation for Natural Language Understanding Tasks
Authors: Sebastian Schuster, Christopher D. Manning
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Implicit Relations, Natural Language Understanding

Many shallow natural language understanding tasks use dependency trees to extract relations between content words. However, strict surface-structure dependency trees tend to follow the linguistic structure of sentences too closely and frequently fail to provide direct relations between content words. To mitigate this problem, the original Stanford Dependencies representation also defines two dependency graph representations which contain additional and augmented relations that explicitly capture otherwise implicit relations between content words. In this paper, we revisit and extend these dependency graph representations in light of the recent Universal Dependencies (UD) initiative and provide a detailed account of an enhanced and an enhanced++ English UD representation. We further present a converter from constituency to basic, i.e., strict surface structure, UD trees, and a converter from basic UD trees to enhanced and enhanced++ English UD graphs. We release both converters as part of Stanford CoreNLP and the Stanford Parser.
A Proposition Bank of Urdu
Authors: Maaz Anwar, Riyaz Ahmad Bhat, Dipti Sharma, Ashwini Vaidya, Martha Palmer, Tafseer Ahmed Khan
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

This paper describes our efforts for the development of a Proposition Bank for Urdu, an Indo-Aryan language. Our primary goal is the labeling of syntactic nodes in the existing Urdu dependency Treebank with specific argument labels. In essence, it involves annotation of predicate argument structures of both simple and complex predicates in the Treebank corpus. We describe the overall process of building the PropBank of Urdu. We discuss various statistics pertaining to the Urdu PropBank and the issues which the annotators encountered while developing the PropBank. We also discuss how these challenges were addressed to successfully expand the PropBank corpus. While reporting the Inter-annotator agreement between the two annotators, we show that the annotators share similar understanding of the annotation guidelines and of the linguistic phenomena present in the language. The present size of this Propbank is around 180,000 tokens which is double-propbanked by the two annotators for simple predicates. Another 100,000 tokens have been annotated for complex predicates of Urdu.
Czech Legal Text Treebank 1.0
Authors: Vincent Kr{\'\i}{\v{z}}, Barbora Hladk{\'a}, Zde{\v{n}}ka Ure{\v{s}}ov{\'a}
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

We introduce a new member of the family of Prague dependency treebanks. The Czech Legal Text Treebank 1.0 is a morphologically and syntactically annotated corpus of 1,128 sentences. The treebank contains texts from the legal domain, namely the documents from the Collection of Laws of the Czech Republic. Legal texts differ from other domains in several language phenomena influenced by rather high frequency of very long sentences. A manual annotation of such sentences presents a new challenge. We describe a strategy and tools for this task. The resulting treebank can be explored in various ways. It can be downloaded from the LINDAT/CLARIN repository and viewed locally using the TrEd editor or it can be accessed on-line using the KonText and TreeQuery tools.
Concepticon: A Resource for the Linking of Concept Lists
Authors: Johann-Mattis List, Michael Cysouw, Robert Forkel
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

We present an attempt to link the large amount of different concept lists which are used in the linguistic literature, ranging from Swadesh lists in historical linguistics to naming tests in clinical studies and psycholinguistics. This resource, our Concepticon, links 30 222 concept labels from 160 conceptlists to 2495 concept sets. Each concept set is given a unique identifier, a unique label, and a human-readable definition. Concept sets are further structured by defining different relations between the concepts. The resource can be used for various purposes. Serving as a rich reference for new and existing databases in diachronic and synchronic linguistics, it allows researchers a quick access to studies on semantic change, cross-linguistic polysemies, and semantic associations.
LVF-lemon â€• Towards a Linked Data Representation of ``Les Verbes fran\ccais''
Authors: Ingrid Falk, Achim Stein
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

In this study we elaborate a road map for the conversion of a traditional lexical syntactico-semantic resource for French into a linguistic linked open data (LLOD) model. Our approach uses current best-practices and the analyses of earlier similar undertakings (lemonUBY and PDEV-lemon) to tease out the most appropriate representation for our resource.
Riddle Generation using Word Associations
Authors: Paloma Galv{\'a}n, Virginia Francisco, Raquel Herv{\'a}s, Gonzalo M{\'e}ndez
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

In knowledge bases where concepts have associated properties, there is a large amount of comparative information that is implicitly encoded in the values of the properties these concepts share. Although there have been previous approaches to generating riddles, none of them seem to take advantage of structured information stored in knowledge bases such as Thesaurus Rex, which organizes concepts according to the fine grained ad-hoc categories they are placed into by speakers in everyday language, along with associated properties or modifiers. Taking advantage of these shared properties, we have developed a riddle generator that creates riddles about concepts represented as common nouns. The base of these riddles are comparisons between the target concept and other entities that share some of its properties. In this paper, we describe the process we have followed to generate the riddles starting from the target concept and we show the results of the first evaluation we have carried out to test the quality of the resulting riddles.
Challenges of Adjective Mapping between plWordNet and Princeton WordNet
Authors: Ewa Rudnicka, Wojciech Witkowski, Katarzyna Podlaska
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

The paper presents the strategy and results of mapping adjective synsets between plWordNet (the wordnet of Polish, cf. Piasecki et al. 2009, Maziarz et al. 2013) and Princeton WordNet (cf. Fellbaum 1998). The main challenge of this enterprise has been very different synset relation structures in the two networks: horizontal, dumbbell-model based in PWN and vertical, hyponymy-based in plWN. Moreover, the two wordnets display differences in the grouping of adjectives into semantic domains and in the size of the adjective category. The handle the above contrasts, a series of automatic prompt algorithms and a manual mapping procedure relying on corresponding synset and lexical unit relations as well as on inter-lingual relations between noun synsets were proposed in the pilot stage of mapping (Rudnicka et al. 2015). In the paper we discuss the final results of the mapping process as well as explain example mapping choices. Suggestions for further development of mapping are also given.
Relation- and Phrase-level Linking of FrameNet with Sar-graphs
Authors: Aleks Gabryszak, ra, Sebastian Krause, Leonhard Hennig, Feiyu Xu, Hans Uszkoreit
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Knowledge Graphs, Relation, Relation Extraction

Recent research shows the importance of linking linguistic knowledge resources for the creation of large-scale linguistic data. We describe our approach for combining two English resources, FrameNet and sar-graphs, and illustrate the benefits of the linked data in a relation extraction setting. While FrameNet consists of schematic representations of situations, linked to lexemes and their valency patterns, sar-graphs are knowledge resources that connect semantic relations from factual knowledge graphs to the linguistic phrases used to express instances of these relations. We analyze the conceptual similarities and differences of both resources and propose to link sar-graphs and FrameNet on the levels of relations/frames as well as phrases. The former alignment involves a manual ontology mapping step, which allows us to extend sar-graphs with new phrase patterns from FrameNet. The phrase-level linking, on the other hand, is fully automatic. We investigate the quality of the automatically constructed links and identify two main classes of errors.
Mapping Ontologies Using Ontologies: Cross-lingual Semantic Role Information Transfer
Authors: Bal{\'a}zs Indig, M{\'a}rton Mih{\'a}ltz, Andr{\'a}s Simonyi
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Logical Reasoning

This paper presents the process of enriching the verb frame database of a Hungarian natural language parser to enable the assignment of semantic roles. We accomplished this by linking the parser{'}s verb frame database to existing linguistic resources such as VerbNet and WordNet, and automatically transferring back semantic knowledge. We developed OWL ontologies that map the various constraint description formalisms of the linked resources and employed a logical reasoning device to facilitate the linking procedure. We present results and discuss the challenges and pitfalls that arose from this undertaking.
Generating a Large-Scale Entity Linking Dictionary from Wikipedia Link Structure and Article Text
Authors: Ravindra Harige, Paul Buitelaar
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Entity Linking

Wikipedia has been increasingly used as a knowledge base for open-domain Named Entity Linking and Disambiguation. In this task, a dictionary with entity surface forms plays an important role in finding a set of candidate entities for the mentions in text. Existing dictionaries mostly rely on the Wikipedia link structure, like anchor texts, redirect links and disambiguation links. In this paper, we introduce a dictionary for Entity Linking that includes name variations extracted from Wikipedia article text, in addition to name variations derived from the Wikipedia link structure. With this approach, we show an increase in the coverage of entities and their mentions in the dictionary in comparison to other Wikipedia based dictionaries.
The Open Linguistics Working Group: Developing the Linguistic Linked Open Data Cloud
Authors: John Philip McCrae, Christian Chiarcos, Francis Bond, Philipp Cimiano, Thierry Declerck, Gerard de Melo, Jorge Gracia, Sebastian Hellmann, Bettina Klimek, Steven Moran, Petya Osenova, Antonio Pareja-Lora, Jonathan Pool
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

The Open Linguistics Working Group (OWLG) brings together researchers from various fields of linguistics, natural language processing, and information technology to present and discuss principles, case studies, and best practices for representing, publishing and linking linguistic data collections. A major outcome of our work is the Linguistic Linked Open Data (LLOD) cloud, an LOD (sub-)cloud of linguistic resources, which covers various linguistic databases, lexicons, corpora, terminologies, and metadata repositories. We present and summarize five years of progress on the development of the cloud and of advancements in open data in linguistics, and we describe recent community activities. The paper aims to serve as a guideline to orient and involve researchers with the community and/or Linguistic Linked Open Data.
Cross-lingual RDF Thesauri Interlinking
Authors: Tatiana Lesnikova, J{\'e}r{\^o}me David, J{\'e}r{\^o}me Euzenat
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Machine Translation, Translation

Various lexical resources are being published in RDF. To enhance the usability of these resources, identical resources in different data sets should be linked. If lexical resources are described in different natural languages, then techniques to deal with multilinguality are required for interlinking. In this paper, we evaluate machine translation for interlinking concepts, i.e., generic entities named with a common noun or term. In our previous work, the evaluated method has been applied on named entities. We conduct two experiments involving different thesauri in different languages. The first experiment involves concepts from the TheSoz multilingual thesaurus in three languages: English, French and German. The second experiment involves concepts from the EuroVoc and AGROVOC thesauri in English and Chinese respectively. Our results demonstrate that machine translation can be beneficial for cross-lingual thesauri interlinking independently of a dataset structure.
The Language Resource Life Cycle: Towards a Generic Model for Creating, Maintaining, Using and Distributing Language Resources
Authors: Georg Rehm
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Management

Language Resources (LRs) are an essential ingredient of current approaches in Linguistics, Computational Linguistics, Language Technology and related fields. LRs are collections of spoken or written language data, typically annotated with linguistic analysis information. Different types of LRs exist, for example, corpora, ontologies, lexicons, collections of spoken language data (audio), or collections that also include video (multimedia, multimodal). Often, LRs are distributed with specific tools, documentation, manuals or research publications. The different phases that involve creating and distributing an LR can be conceptualised as a life cycle. While the idea of handling the LR production and maintenance process in terms of a life cycle has been brought up quite some time ago, a best practice model or common approach can still be considered a research gap. This article wants to help fill this gap by proposing an initial version of a generic Language Resource Life Cycle that can be used to inform, direct, control and evaluate LR research and development activities (including description, management, production, validation and evaluation workflows).