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- item-1 hasContent joachim-gasch.
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- item-2 hasContent caren-brinckmann.
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- item-3 hasContent sylvia-dickgiesser.
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- 73 creator diana-santos.
- 73 creator maria-do-rosario-silva.
- 73 creator susana-inacio.
- 73 type InProceedings.
- 73 label "What s in a Colour? Studying and Contrasting Colours with COMPARA".
- 73 sameAs 73.
- 73 abstract "In this paper we present contrastive colour studies done using COMPARA, the largest edited parallel corpus in the world (as far as we know). The studies were the result of semantic annotation of the corpus in this domain. We chose to start with colour because it is a relatively contained lexical category and the subject of many arguments in linguistics. We begin by explaining the criteria involved in the annotation process, not only for the colour categories but also for the colour groups created in order to do finer-grained analyses, presenting also some quantitative data regarding these categories and groups. We proceed to compare the two languages according to the diversity of available lexical items, morphological and syntactic properties, and then try to understand the translation of colour. We end by explaining how any user who wants to do serious studies using the corpus can collaborate in enhancing the corpus and making their semantic annotations widely available as well.".
- 73 hasAuthorList authorList.
- 73 hasTopic Linguistics.
- 73 isPartOf proceedings.
- 73 keyword "Corpus (creation, annotation, etc.)".
- 73 keyword "Multilinguality".
- 73 keyword "Semantics".
- 73 title "What s in a Colour? Studying and Contrasting Colours with COMPARA".
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- item-1 hasContent diana-santos.
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- item-2 hasContent maria-do-rosario-silva.
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- item-3 hasContent susana-inacio.
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- 732 creator anca-dinu.
- 732 type InProceedings.
- 732 label "On Classifying Coherent/Incoherent Romanian Short Texts".
- 732 sameAs 732.
- 732 abstract "In this paper we present and discuss the results of a text coherence experiment performed on a small corpus of Romanian text from a number of alternative high school manuals. During the last 10 years, an abundance of alternative manuals for high school was produced and distributed in Romania. Due to the large amount of material and to the relative short time in which it was produced, the question of assessing the quality of this material emerged; this process relied mostly of subjective human personal opinion, given the lack of automatic tools for Romanian. Debates and claims of poor quality of the alternative manuals resulted in a number of examples of incomprehensible / incoherent paragraphs extracted from such manuals. Our goal was to create an automatic tool which may be used as an indication of poor quality of such texts. We created a small corpus of representative texts from Romanian alternative manuals. We manually classified the chosen paragraphs from such manuals into two categories: comprehensible/coherent text and incomprehensible/incoherent text. We then used different machine learning techniques to automatically classify them in a supervised manner. Our approach is rather simple, but the results are encouraging.".
- 732 hasAuthorList authorList.
- 732 hasTopic Linguistics.
- 732 isPartOf proceedings.
- 732 keyword "Acquisition, Machine Learning".
- 732 keyword "Document Classification, Text categorisation".
- 732 keyword "Semantics".
- 732 title "On Classifying Coherent/Incoherent Romanian Short Texts".
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- item-1 hasContent anca-dinu.
- 733 creator andreas-eisele.
- 733 creator martin-kay.
- 733 creator yu-chen.
- 733 type InProceedings.
- 733 label "Improving Statistical Machine Translation Efficiency by Triangulation".
- 733 sameAs 733.
- 733 abstract "In current phrase-based Statistical Machine Translation systems, more training data is generally better than less. However, a larger data set eventually introduces a larger model that enlarges the search space for the decoder, and consequently requires more time and more resources to translate. This paper describes an attempt to reduce the model size by filtering out the less probable entries based on testing correlation using additional training data in an intermediate third language. The central idea behind the approach is triangulation, the process of incorporating multilingual knowledge in a single system, which eventually utilizes parallel corpora available in more than two languages. We conducted experiments using Europarl corpus to evaluate our approach. The reduction of the model size can be up to 70% while the translation quality is being preserved.".
- 733 hasAuthorList authorList.
- 733 hasTopic Linguistics.
- 733 isPartOf proceedings.
- 733 keyword "Machine Translation, SpeechToSpeech Translation".
- 733 keyword "Multilinguality".
- 733 keyword "Statistical methods".
- 733 title "Improving Statistical Machine Translation Efficiency by Triangulation".
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- item-1 hasContent yu-chen.
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- item-2 hasContent andreas-eisele.
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- item-3 hasContent martin-kay.
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- 734 creator cosmin-bejan.
- 734 creator sanda-harabagiu.
- 734 type InProceedings.
- 734 label "A Linguistic Resource for Discovering Event Structures and Resolving Event Coreference".
- 734 sameAs 734.
- 734 abstract "In this paper, we present a linguistic resource that annotates event structures in texts. We consider an event structure as a collection of events that interact with each other in a given situation. We interpret the interactions between events as event relations. In this regard, we propose and annotate a set of six relations that best capture the concept of event structure. These relations are: subevent, reason, purpose, enablement, precedence and related. A document from this resource can encode multiple event structures and an event structure can be described across multiple documents. In order to unify event structures, we also annotate inter- and intra-document event coreference. Moreover, we provide methodologies for automatic discovery of event structures from texts. First, we group the events that constitute an event structure into event clusters and then, we use supervised learning frameworks to classify the relations that exist between events from the same cluster".
- 734 hasAuthorList authorList.
- 734 hasTopic Linguistics.
- 734 isPartOf proceedings.
- 734 keyword "Corpus (creation, annotation, etc.)".
- 734 keyword "Knowledge representation".
- 734 keyword "Ontologies".
- 734 title "A Linguistic Resource for Discovering Event Structures and Resolving Event Coreference".