Paper Group NANR 109
Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V). Pattern-based Word Sketches for the Extraction of Semantic Relations. T=ezaurs.lv: the Largest Open Lexical Database for Latvian. Detecting late-life depression in Alzheimer’s disease through analysis of speech and language. Proceedings of the Third International Wo …
Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)
| Title | Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V) |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-5300/ |
| https://www.aclweb.org/anthology/W16-5300 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-5th-workshop-on-cognitive-1 |
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Pattern-based Word Sketches for the Extraction of Semantic Relations
| Title | Pattern-based Word Sketches for the Extraction of Semantic Relations |
| Authors | Pilar Le{'o}n-Ara{'u}z, Antonio San Mart{'\i}n, Pamela Faber |
| Abstract | Despite advances in computer technology, terminologists still tend to rely on manual work to extract all the semantic information that they need for the description of specialized concepts. In this paper we propose the creation of new word sketches in Sketch Engine for the extraction of semantic relations. Following a pattern-based approach, new sketch grammars are devel-oped in order to extract some of the most common semantic relations used in the field of ter-minology: generic-specific, part-whole, location, cause and function. |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4709/ |
| https://www.aclweb.org/anthology/W16-4709 | |
| PWC | https://paperswithcode.com/paper/pattern-based-word-sketches-for-the |
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T=ezaurs.lv: the Largest Open Lexical Database for Latvian
| Title | T=ezaurs.lv: the Largest Open Lexical Database for Latvian |
| Authors | Andrejs Spektors, Ilze Auzina, Roberts Dargis, Normunds Gruzitis, Peteris Paikens, Lauma Pretkalnina, Laura Rituma, Baiba Saulite |
| Abstract | We describe an extensive and versatile lexical resource for Latvian, an under-resourced Indo-European language, which we call Tezaurs (Latvian for {`}thesaurus{'}). It comprises a large explanatory dictionary of more than 250,000 entries that are derived from more than 280 external sources. The dictionary is enriched with phonetic, morphological, semantic and other annotations, as well as augmented by various language processing tools allowing for the generation of inflectional forms and pronunciation, for on-the-fly selection of corpus examples, for suggesting synonyms, etc. Tezaurs is available as a public and widely used web application for end-users, as an open data set for the use in language technology (LT), and as an API ― a set of web services for the integration into third-party applications. The ultimate goal of Tezaurs is to be the central computational lexicon for Latvian, bringing together all Latvian words and frequently used multi-word units and allowing for the integration of other LT resources and tools. | |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1408/ |
| https://www.aclweb.org/anthology/L16-1408 | |
| PWC | https://paperswithcode.com/paper/tezaurslv-the-largest-open-lexical-database |
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Detecting late-life depression in Alzheimer’s disease through analysis of speech and language
| Title | Detecting late-life depression in Alzheimer’s disease through analysis of speech and language |
| Authors | Kathleen C. Fraser, Frank Rudzicz, Graeme Hirst |
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| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0301/ |
| https://www.aclweb.org/anthology/W16-0301 | |
| PWC | https://paperswithcode.com/paper/detecting-late-life-depression-in-alzheimers |
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Proceedings of the Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies (WLSI/OIAF4HLT2016)
| Title | Proceedings of the Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies (WLSI/OIAF4HLT2016) |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-5200/ |
| https://www.aclweb.org/anthology/W16-5200 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-third-international-3 |
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OCLSP at SemEval-2016 Task 9: Multilayered LSTM as a Neural Semantic Dependency Parser
| Title | OCLSP at SemEval-2016 Task 9: Multilayered LSTM as a Neural Semantic Dependency Parser |
| Authors | Lifeng Jin, Manjuan Duan, William Schuler |
| Abstract | |
| Tasks | Dependency Parsing, Machine Translation |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1188/ |
| https://www.aclweb.org/anthology/S16-1188 | |
| PWC | https://paperswithcode.com/paper/oclsp-at-semeval-2016-task-9-multilayered |
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UCL+Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound
| Title | UCL+Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound |
| Authors | James Goodman, Andreas Vlachos, Jason Naradowsky |
| Abstract | |
| Tasks | Amr Parsing, Imitation Learning, Semantic Parsing |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1180/ |
| https://www.aclweb.org/anthology/S16-1180 | |
| PWC | https://paperswithcode.com/paper/uclsheffield-at-semeval-2016-task-8-imitation |
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On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability
| Title | On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability |
| Authors | Guillaume Papa, Aurélien Bellet, Stephan Clémençon |
| Abstract | The problem of predicting connections between a set of data points finds many applications, in systems biology and social network analysis among others. This paper focuses on the \textit{graph reconstruction} problem, where the prediction rule is obtained by minimizing the average error over all n(n-1)/2 possible pairs of the n nodes of a training graph. Our first contribution is to derive learning rates of order O(log n / n) for this problem, significantly improving upon the slow rates of order O(1/√n) established in the seminal work of Biau & Bleakley (2006). Strikingly, these fast rates are universal, in contrast to similar results known for other statistical learning problems (e.g., classification, density level set estimation, ranking, clustering) which require strong assumptions on the distribution of the data. Motivated by applications to large graphs, our second contribution deals with the computational complexity of graph reconstruction. Specifically, we investigate to which extent the learning rates can be preserved when replacing the empirical reconstruction risk by a computationally cheaper Monte-Carlo version, obtained by sampling with replacement B « n² pairs of nodes. Finally, we illustrate our theoretical results by numerical experiments on synthetic and real graphs. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6588-on-graph-reconstruction-via-empirical-risk-minimization-fast-learning-rates-and-scalability |
| http://papers.nips.cc/paper/6588-on-graph-reconstruction-via-empirical-risk-minimization-fast-learning-rates-and-scalability.pdf | |
| PWC | https://paperswithcode.com/paper/on-graph-reconstruction-via-empirical-risk |
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Learning Event Expressions via Bilingual Structure Projection
| Title | Learning Event Expressions via Bilingual Structure Projection |
| Authors | Fangyuan Li, Ruihong Huang, Deyi Xiong, Min Zhang |
| Abstract | Identifying events of a specific type is a challenging task as events in texts are described in numerous and diverse ways. Aiming to resolve high complexities of event descriptions, previous work (Huang and Riloff, 2013) proposes multi-faceted event recognition and a bootstrapping method to automatically acquire both event facet phrases and event expressions from unannotated texts. However, to ensure high quality of learned phrases, this method is constrained to only learn phrases that match certain syntactic structures. In this paper, we propose a bilingual structure projection algorithm that explores linguistic divergences between two languages (Chinese and English) and mines new phrases with new syntactic structures, which have been ignored in the previous work. Experiments show that our approach can successfully find novel event phrases and structures, e.g., phrases headed by nouns. Furthermore, the newly mined phrases are capable of recognizing additional event descriptions and increasing the recall of event recognition. |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1136/ |
| https://www.aclweb.org/anthology/C16-1136 | |
| PWC | https://paperswithcode.com/paper/learning-event-expressions-via-bilingual |
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Detection of Major ASL Sign Types in Continuous Signing For ASL Recognition
| Title | Detection of Major ASL Sign Types in Continuous Signing For ASL Recognition |
| Authors | Polina Yanovich, Carol Neidle, Dimitris Metaxas |
| Abstract | In American Sign Language (ASL) as well as other signed languages, different classes of signs (e.g., lexical signs, fingerspelled signs, and classifier constructions) have different internal structural properties. Continuous sign recognition accuracy can be improved through use of distinct recognition strategies, as well as different training datasets, for each class of signs. For these strategies to be applied, continuous signing video needs to be segmented into parts corresponding to particular classes of signs. In this paper we present a multiple instance learning-based segmentation system that accurately labels 91.27{%} of the video frames of 500 continuous utterances (including 7 different subjects) from the publicly accessible NCSLGR corpus (Neidle and Vogler, 2012). The system uses novel feature descriptors derived from both motion and shape statistics of the regions of high local motion. The system does not require a hand tracker. |
| Tasks | Multiple Instance Learning |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1490/ |
| https://www.aclweb.org/anthology/L16-1490 | |
| PWC | https://paperswithcode.com/paper/detection-of-major-asl-sign-types-in |
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CogALex-V Shared Task: HsH-Supervised – Supervised similarity learning using entry wise product of context vectors
| Title | CogALex-V Shared Task: HsH-Supervised – Supervised similarity learning using entry wise product of context vectors |
| Authors | Christian Wartena, Rosa Tsegaye Aga |
| Abstract | The CogALex-V Shared Task provides two datasets that consists of pairs of words along with a classification of their semantic relation. The dataset for the first task distinguishes only between related and unrelated, while the second data set distinguishes several types of semantic relations. A number of recent papers propose to construct a feature vector that represents a pair of words by applying a pairwise simple operation to all elements of the feature vector. Subsequently, the pairs can be classified by training any classification algorithm on these vectors. In the present paper we apply this method to the provided datasets. We see that the results are not better than from the given simple baseline. We conclude that the results of the investigated method are strongly depended on the type of data to which it is applied. |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-5316/ |
| https://www.aclweb.org/anthology/W16-5316 | |
| PWC | https://paperswithcode.com/paper/cogalex-v-shared-task-hsh-supervised-a |
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Evaluating Entity Linking: An Analysis of Current Benchmark Datasets and a Roadmap for Doing a Better Job
| Title | Evaluating Entity Linking: An Analysis of Current Benchmark Datasets and a Roadmap for Doing a Better Job |
| Authors | Marieke van Erp, Pablo Mendes, Heiko Paulheim, Filip Ilievski, Julien Plu, Giuseppe Rizzo, Joerg Waitelonis |
| Abstract | Entity linking has become a popular task in both natural language processing and semantic web communities. However, we find that the benchmark datasets for entity linking tasks do not accurately evaluate entity linking systems. In this paper, we aim to chart the strengths and weaknesses of current benchmark datasets and sketch a roadmap for the community to devise better benchmark datasets. |
| Tasks | Entity Linking |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1693/ |
| https://www.aclweb.org/anthology/L16-1693 | |
| PWC | https://paperswithcode.com/paper/evaluating-entity-linking-an-analysis-of |
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EasyTree: A Graphical Tool for Dependency Tree Annotation
| Title | EasyTree: A Graphical Tool for Dependency Tree Annotation |
| Authors | Alexa Little, Stephen Tratz |
| Abstract | 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. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1371/ |
| https://www.aclweb.org/anthology/L16-1371 | |
| PWC | https://paperswithcode.com/paper/easytree-a-graphical-tool-for-dependency-tree |
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Evaluating Word Embeddings Using a Representative Suite of Practical Tasks
| Title | Evaluating Word Embeddings Using a Representative Suite of Practical Tasks |
| Authors | Neha Nayak, Gabor Angeli, Christopher D. Manning |
| Abstract | |
| Tasks | Word Embeddings |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2504/ |
| https://www.aclweb.org/anthology/W16-2504 | |
| PWC | https://paperswithcode.com/paper/evaluating-word-embeddings-using-a |
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USAAR at SemEval-2016 Task 13: Hyponym Endocentricity
| Title | USAAR at SemEval-2016 Task 13: Hyponym Endocentricity |
| Authors | Liling Tan, Francis Bond, Josef van Genabith |
| Abstract | |
| Tasks | Word Embeddings |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1203/ |
| https://www.aclweb.org/anthology/S16-1203 | |
| PWC | https://paperswithcode.com/paper/usaar-at-semeval-2016-task-13-hyponym |
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