pwc-archive/papers-with-abstracts huggingface dataset:
Event Nominals: Annotation Guidelines and a Manually Annotated Corpus in French
Authors: B{\'e}atrice Arnulphy, Xavier Tannier, Anne Vilnat
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Articles

Within the general purpose of information extraction, detection of event descriptions is an important clue. A word refering to an event is more powerful than a single word, because it implies a location, a time, protagonists (persons, organizations{\textbackslash}dots). However, if verbal designations of events are well studied and easier to detect than nominal ones, nominal designations do not claim as much definition effort and resources. In this work, we focus on nominals desribing events. As our application domain is information extraction, we follow a named entity approach to describe and annotate events. In this paper, we present a typology and annotation guidelines for event nominals annotation. We applied them to French newswire articles and produced an annotated corpus. We present observations about the designations used in our manually annotated corpus and the behavior of their triggers. We provide statistics concerning word ambiguity and context of use of event nominals, as well as machine learning experiments showing the difficulty of using lexicons for extracting events.
Comparison between two models of language for the automatic phonetic labeling of an undocumented language of the South-Asia: the case of Mo Piu
Authors: Genevi{\`e}ve Caelen-Haumont, Sethserey Sam
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Language Modelling

This paper aims at assessing the automatic labeling of an undocumented, unknown, unwritten and under-resourced language (Mo Piu) of the North Vietnam, by an expert phonetician. In the previous stage of the work, 7 sets of languages were chosen among Mandarin, Vietnamese, Khmer, English, French, to compete in order to select the best models of languages to be used for the phonetic labeling of Mo Piu isolated words. Two sets of languages (1{\^A}{\mbox{$^\circ$}} Mandarin + French, 2{\^A}{\mbox{$^\circ$}} Vietnamese + French) which got the best scores showed an additional distribution of their results. Our aim is now to study this distribution more precisely and more extensively, in order to statistically select the best models of languages and among them, the best sets of phonetic units which minimize the wrong phonetic automatic labeling.
The Parallel-TUT: a multilingual and multiformat treebank
Authors: Cristina Bosco, Manuela Sanguinetti, Leonardo Lesmo
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation

The paper introduces an ongoing project for the development of a parallel treebank for Italian, English and French, i.e. Parallel--TUT, or simply ParTUT. For the development of this resource, both the dependency and constituency-based formats of the Italian Turin University Treebank (TUT) have been applied to a preliminary dataset, which includes the whole text of the Universal Declaration of Human Rights, and sentences from the JRC-Acquis Multilingual Parallel Corpus and the Creative Commons licence. The focus of the project is mainly on the quality of the annotation and the investigation of some issues related to the alignment of data that can be allowed by the TUT formats, also taking into account the availability of conversion tools for display data in standard ways, such as Tiger--XML and CoNLL formats. It is, in fact, our belief that increasing the portability of our treebank could give us the opportunity to access resources and tools provided by other research groups, especially at this stage of the project, where no particular tool -- compatible with the TUT format -- is available in order to tackle the alignment problems.
Leveraging the Wisdom of the Crowds for the Acquisition of Multilingual Language Resources
Authors: Arno Scharl, Marta Sabou, Stefan Gindl, Walter Rafelsberger, Albert Weichselbraun
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

Games with a purpose are an increasingly popular mechanism for leveraging the wisdom of the crowds to address tasks which are trivial for humans but still not solvable by computer algorithms in a satisfying manner. As a novel mechanism for structuring human-computer interactions, a key challenge when creating them is motivating users to participate while generating useful and unbiased results. This paper focuses on important design choices and success factors of effective games with a purpose. Our findings are based on lessons learned while developing and deploying Sentiment Quiz, a crowdsourcing application for creating sentiment lexicons (an essential component of most sentiment detection algorithms). We describe the goals and structure of the game, the underlying application framework, the sentiment lexicons gathered through crowdsourcing, as well as a novel approach to automatically extend the lexicons by means of a bootstrapping process. Such an automated extension further increases the efficiency of the acquisition process by limiting the number of terms that need to be gathered from the game participants.
Using multimodal resources for explanation approaches in intelligent systems
Authors: Florian Nothdurft, Wolfgang Minker
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this work we show that there is a need of using multimodal resources during human-computer interaction (HCI) in intelligent systems. We propose that not only creating multimodal output for the user is important, but to take multimodal input resources into account for the decision when and how to interact. Especially the use of multimodal input resources for the decision when and how to provide assistance in HCI is important. The use of assistive functionalities like providing adaptive explanations to keep the user motivated and cooperative is more than a side-effect and demands a closer look. In this paper we introduce our approach on how to use multimodal input ressources in an adaptive and generic explanation pipeline. We do not only concentrate on using explanations as a way to manage user knowledge, but to maintain the cooperativeness, trust and motivation of the user to continue a healthy and well-structured HCI.
Cloud Logic Programming for Integrating Language Technology Resources
Authors: Markus Forsberg, Torbj{\"o}rn Lager
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The main goal of the CLT Cloud project is to equip lexica, morphological processors, parsers and other software components developed within CLT (Centre of Language Technology) with so called web API:s, thus making them available on the Internet in the form of web services. We present a proof-of-concept implementation of the CLT Cloud server where we use the logic programming language Prolog for composing and aggregating existing web services into new web services in a way that encourages creative exploration and rapid prototyping of LT applications.
AnIta: a powerful morphological analyser for Italian
Authors: Fabio Tamburini, Mel, Matias ri
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Management, POS

In this paper we present AnIta, a powerful morphological analyser for Italian implemented within the framework of finite-state-automata models. It is provided by a large lexicon containing more than 110,000 lemmas that enable it to cover relevant portions of Italian texts. We describe our design choices for the management of inflectional phenomena as well as some interesting new features to explicitly handle derivational and compositional processes in Italian, namely the wordform segmentation structure and Derivation Graph. Two different evaluation experiments, for testing coverage (Recall) and Precision, are described in detail, comparing the AnIta performances with some other freely available tools to handle Italian morphology. The experiments results show that the AnIta Morphological Analyser obtains the best performances among the tested systems, with Recall = 97.21{\%} and Precision = 98.71{\%}. This tool was a fundamental building block for designing a performant PoS-tagger and Lemmatiser for the Italian language that participated to two EVALITA evaluation campaigns ranking, in both cases, together with the best performing systems.
Automatic classification of German \textitan particle verbs
Authors: Sylvia Springorum, Sabine Schulte im Walde, Antje Ro{\ss}deutscher
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Classification, General Classification

The current study works at the interface of theoretical and computational linguistics to explore the semantic properties of an particle verbs, i.e., German particle verbs with the particle an. Based on a thorough analysis of the particle verbs from a theoretical point of view, we identified empirical features and performed an automatic semantic classification. A focus of the study was on the mutual profit of theoretical and empirical perspectives with respect to salient semantic properties of the an particle verbs: (a) how can we transform the theoretical insights into empirical, corpus-based features, (b) to what extent can we replicate the theoretical classification by a machine learning approach, and (c) can the computational analysis in turn deepen our insights to the semantic properties of the particle verbs? The best classification result of 70{\%} correct class assignments was reached through a GermaNet-based generalization of direct object nouns plus a prepositional phrase feature. These particle verb features in combination with a detailed analysis of the results at the same time confirmed and enlarged our knowledge about salient properties.
LIE: Leadership, Influence and Expertise
Authors: Roberta Catizone, Louise Guthrie, Arthur Thomas, Yorick Wilks
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper describes our research into methods for inferring social and instrumental roles and relationships from document and discourse corpora. The goal is to identify the roles of initial authors and participants in internet discussions with respect to leadership, influence and expertise. Web documents, forums and blogs provide data from which the relationships between these concepts are empirically derived and compared. Using techniques from Natural Language Processing (NLP), characterizations of authority and expertise are hypothesized and then tested to see if these pick out the same or different participants as may be chosen by techniques based on social network analysis (Huffaker 2010) see if they pick out the same discourse participants for any given level of these qualities (i.e. leadership, expertise and influence). Our methods could be applied, in principle, to any domain topic, but this paper will describe an initial investigation into two subject areas where a range of differing opinions are available and which differ in the nature of their appeals to authority and truth: genetic engineering' and a Muslim Forum'. The available online corpora for these topics contain discussions from a variety of users with different levels of expertise, backgrounds and personalities.
CAT: the CELCT Annotation Tool
Authors: Valentina Bartalesi Lenzi, Giovanni Moretti, Rachele Sprugnoli
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Management, text annotation

This paper presents CAT - CELCT Annotation Tool, a new general-purpose web-based tool for text annotation developed by CELCT (Center for the Evaluation of Language and Communication Technologies). The aim of CAT is to make text annotation an intuitive, easy and fast process. In particular, CAT was created to support human annotators in performing linguistic and semantic text annotation and was designed to improve productivity and reduce time spent on this task. Manual text annotation is, in fact, a time-consuming activity, and conflicts may arise with the strict deadlines annotation projects are frequently subject to. Thanks to its adaptability and user-friendly interface, CAT can positively contribute to improve time management in annotation project. Further, the tool has a number of features which make it an easy-to-use tool for many types of annotations. Even if the first prototype of CAT has been used to perform temporal and event annotation following the It-TimeML specifications, the tool is general enough to be used for annotating a broad range of linguistic and semantic phenomena. CAT is freely available for research purposes.
Quantising Opinions for Political Tweets Analysis
Authors: Yulan He, Hassan Saif, Zhongyu Wei, Kam-Fai Wong
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Sentiment Analysis

There have been increasing interests in recent years in analyzing tweet messages relevant to political events so as to understand public opinions towards certain political issues. We analyzed tweet messages crawled during the eight weeks leading to the UK General Election in May 2010 and found that activities at Twitter is not necessarily a good predictor of popularity of political parties. We then proceed to propose a statistical model for sentiment detection with side information such as emoticons and hash tags implying tweet polarities being incorporated. Our results show that sentiment analysis based on a simple keyword matching against a sentiment lexicon or a supervised classifier trained with distant supervision does not correlate well with the actual election results. However, using our proposed statistical model for sentiment analysis, we were able to map the public opinion in Twitter with the actual offline sentiment in real world.
ROMBAC: The Romanian Balanced Annotated Corpus
Authors: Radu Ion, Elena Irimia, Dan {\c{S}}tef{\u{a}}nescu, Dan Tufi{\textcommabelow{s}}
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Chunking, Lemmatization, POS, POS Tagging

This article describes the collecting, processing and validation of a large balanced corpus for Romanian. The annotation types and structure of the corpus are briefly reviewed. It was constructed at the Research Institute for Artificial Intelligence of the Romanian Academy in the context of an international project (METANET4U). The processing covers tokenization, POS-tagging, lemmatization and chunking. The corpus is in XML format generated by our in-house annotation tools; the corpus encoding schema is XCES compliant and the metadata specification is conformant to the METANET recommendations. To the best of our knowledge, this is the first large and richly annotated corpus for Romanian. ROMBAC is intended to be the foundation of a linguistic environment containing a reference corpus for contemporary Romanian and a comprehensive collection of interoperable processing tools.
Task-Driven Linguistic Analysis based on an Underspecified Features Representation
Authors: Stasinos Konstantopoulos, Valia Kordoni, Nicola Cancedda, Vangelis Karkaletsis, Dietrich Klakow, Jean-Michel Renders
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper we explore a task-driven approach to interfacing NLP components, where language processing is guided by the end-task that each application requires. The core idea is to generalize feature values into feature value distributions, representing under-specified feature values, and to fit linguistic pipelines with a back-channel of specification requests through which subsequent components can declare to preceding ones the importance of narrowing the value distribution of particular features that are critical for the current task.
A French Fairy Tale Corpus syntactically and semantically annotated
Authors: Isma{\"\i}l El Maarouf, Jeanne Villaneau
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Ontology Matching, Relation Extraction, Text Classification

Fairy tales, folktales and more generally children stories have lately attracted the Natural Language Processing (NLP) community. As such, very few corpora exist and linguistic resources are lacking. The work presented in this paper aims at filling this gap by presenting a syntactically and semantically annotated corpus. It focuses on the linguistic analysis of a Fairy Tales Corpus, and provides the description of the syntactic and semantic resources developed for Information Extraction. Resources include syntactic dependency relation annotation for 120 verbs; referential annotation, which is concerned with annotating each anaphoric occurrence and Proper Name with the most specific noun in the text; ontology matching for a substantial part of the nouns in the corpus; semantic role labelling for 41 verbs using the FrameNet database. The article also sums up previous analyses of this corpus and indicates possible uses of this corpus for the NLP community.
ConanDoyle-neg: Annotation of negation cues and their scope in Conan Doyle stories
Authors: Roser Morante, Walter Daelemans
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Negation

In this paper we present ConanDoyle-neg, a corpus of stories by Conan Doyle annotated with negation information. The negation cues and their scope, as well as the event or property that is negated have been annotated by two annotators. The inter-annotator agreement is measured in terms of F-scores at scope level. It is higher for cues (94.88 and 92.77), less high for scopes (85.04 and 77.31), and lower for the negated event (79.23 and 80.67). The corpus is publicly available.
GerNED: A German Corpus for Named Entity Disambiguation
Authors: Danuta Ploch, Leonhard Hennig, Angelina Duka, Ernesto William De Luca, Sahin Albayrak
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Articles, Clustering, Coreference Resolution, Entity Disambiguation, Entity Linking, Information Retrieval, Knowledge Base Population, Retrieval, Word Sense Disambiguation

Determining the real-world referents for name mentions of persons, organizations and other named entities in texts has become an important task in many information retrieval scenarios and is referred to as Named Entity Disambiguation (NED). While comprehensive datasets support the development and evaluation of NED approaches for English, there are no public datasets to assess NED systems for other languages, such as German. This paper describes the construction of an NED dataset based on a large corpus of German news articles. The dataset is closely modeled on the datasets used for the Knowledge Base Population tasks of the Text Analysis Conference, and contains gold standard annotations for the NED tasks of Entity Linking, NIL Detection and NIL Clustering. We also present first experimental results on the new dataset for each of these tasks in order to establish a baseline for future research efforts.
A Classification of Adjectives for Polarity Lexicons Enhancement
Authors: Silvia V{\'a}zquez, N{\'u}ria Bel
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Classification, General Classification, Opinion Mining, Sentiment Analysis

Subjective language detection is one of the most important challenges in Sentiment Analysis. Because of the weight and frequency in opinionated texts, adjectives are considered a key piece in the opinion extraction process. These subjective units are more and more frequently collected in polarity lexicons in which they appear annotated with their prior polarity. However, at the moment, any polarity lexicon takes into account prior polarity variations across domains. This paper proves that a majority of adjectives change their prior polarity value depending on the domain. We propose a distinction between domain dependent and domain independent adjectives. Moreover, our analysis led us to propose a further classification related to subjectivity degree: constant, mixed and highly subjective adjectives. Following this classification, polarity values will be a better support for Sentiment Analysis.
A voting scheme to detect semantic underspecification
Authors: H{\'e}ctor Mart{\'\i}nez Alonso, N{\'u}ria Bel, Bolette S. Pedersen, ford
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Word Sense Disambiguation

The following work describes a voting system to automatically classify the sense selection of the complex types Location/Organization and Container/Content, which depend on regular polysemy, as described by the Generative Lexicon (Pustejovsky, 1995) . This kind of sense alternations very often presents semantic underspecificacion between its two possible selected senses. This kind of underspecification is not traditionally contemplated in word sense disambiguation systems, as disambiguation systems are still coping with the need of a representation and recognition of underspecification (Pustejovsky, 2009) The data are characterized by the morphosyntactic and lexical enviroment of the headwords and provided as input for a classifier. The baseline decision tree classifier is compared against an eight-member voting scheme obtained from variants of the training data generated by modifications on the class representation and from two different classification algorithms, namely decision trees and k-nearest neighbors. The voting system improves the accuracy for the non-underspecified senses, but the underspecified sense remains difficult to identify
Aspects of a Legal Framework for Language Resource Management
Authors: Aditi Sharma Grover, Annamart Nieman, Gerhard van Huyssteen, Justus Roux
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Management

The management of language resources requires several legal aspects to be taken into consideration. In this paper we discuss a number of these aspects which lead towards the formation of a legal framework for a language resources management agency. The legal framework entails examination of; the agency's stakeholders and the relationships that exist amongst them, the privacy and intellectual property rights that exist around the language resources offered by the agency, and the external (e.g. laws, acts, policies) and internal legal instruments (e.g. end user licence agreements) required for the agency's operation.
Interplay of Coreference and Discourse Relations: Discourse Connectives with a Referential Component
Authors: Lucie Pol{\'a}kov{\'a}, Pavl{\'\i}na J{\'\i}nov{\'a}, Ji{\v{r}}{\'\i} M{\'\i}rovsk{\'y}
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This contribution explores the subgroup of text structuring expressions with the form preposition + demonstrative pronoun, thus it is devoted to an aspect of the interaction of coreference relations and relations signaled by discourse connectives (DCs) in a text. The demonstrative pronoun typically signals a referential link to an antecedent, whereas the whole expression can, but does not have to, carry a discourse meaning in sense of discourse connectives. We describe the properties of these phrases/expressions with regard to their antecedents, their position among the text-structuring language means and their features typical for the connective function of them compared to their non-connective function. The analysis is carried out on Czech data from the approx. 50,000 sentences of the Prague Dependency Treebank 2.0, directly on the syntactic trees. We explore the characteristics of these phrases/expressions discovered during two projects: the manual annotation of 1, coreference relations (Nedoluzhko et al. 2011) and 2, discourse connectives, their scopes and meanings (Mladov{\'a} et al. 2008).