Paper Group NANR 105
Filling a Knowledge Graph with a Crowd. Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016). Metonymy Analysis Using Associative Relations between Words. Detecting Context Dependence in Exercise Item Candidates Selected from Corpora. UniTN End-to-End Discourse Parser for CoNLL 2016 Shared Task. MAR …
Filling a Knowledge Graph with a Crowd
| Title | Filling a Knowledge Graph with a Crowd |
| Authors | GyuHyeon Choi, Sangha Nam, Dongho Choi, Key-Sun Choi |
| Abstract | |
| Tasks | Knowledge Graphs, Question Answering, Reading Comprehension, Relation Extraction |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4409/ |
| https://www.aclweb.org/anthology/W16-4409 | |
| PWC | https://paperswithcode.com/paper/filling-a-knowledge-graph-with-a-crowd |
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Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016)
| Title | Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016) |
| Authors | |
| Abstract | |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-3700/ |
| https://www.aclweb.org/anthology/W16-3700 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-6th-workshop-on-south-and |
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Metonymy Analysis Using Associative Relations between Words
| Title | Metonymy Analysis Using Associative Relations between Words |
| Authors | Takehiro Teraoka |
| Abstract | Metonymy is a figure of speech in which one item{'}s name represents another item that usually has a close relation with the first one. Metonymic expressions need to be correctly detected and interpreted because sentences including such expressions have different mean- ings from literal ones; computer systems may output inappropriate results in natural language processing. In this paper, an associative approach for analyzing metonymic expressions is proposed. By using associative information and two conceptual distances between words in a sentence, a previous method is enhanced and a decision tree is trained to detect metonymic expressions. After detecting these expressions, they are interpreted as metonymic understanding words by using associative information. This method was evaluated by comparing it with two baseline methods based on previous studies on the Japanese language that used case frames and co-occurrence information. As a result, the proposed method exhibited significantly better accuracy (0.85) of determining words as metonymic or literal expressions than the baselines. It also exhibited better accuracy (0.74) of interpreting the detected metonymic expressions than the baselines. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1731/ |
| https://www.aclweb.org/anthology/L16-1731 | |
| PWC | https://paperswithcode.com/paper/metonymy-analysis-using-associative-relations |
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Detecting Context Dependence in Exercise Item Candidates Selected from Corpora
| Title | Detecting Context Dependence in Exercise Item Candidates Selected from Corpora |
| Authors | Ildik{'o} Pil{'a}n |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0517/ |
| https://www.aclweb.org/anthology/W16-0517 | |
| PWC | https://paperswithcode.com/paper/detecting-context-dependence-in-exercise-item-1 |
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UniTN End-to-End Discourse Parser for CoNLL 2016 Shared Task
| Title | UniTN End-to-End Discourse Parser for CoNLL 2016 Shared Task |
| Authors | Evgeny Stepanov, Giuseppe Riccardi |
| Abstract | |
| Tasks | Model Selection |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/K16-2012/ |
| https://www.aclweb.org/anthology/K16-2012 | |
| PWC | https://paperswithcode.com/paper/unitn-end-to-end-discourse-parser-for-conll |
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MARMOT: A Toolkit for Translation Quality Estimation at the Word Level
| Title | MARMOT: A Toolkit for Translation Quality Estimation at the Word Level |
| Authors | Varvara Logacheva, Chris Hokamp, Lucia Specia |
| Abstract | We present Marmot{\textasciitilde}― a new toolkit for quality estimation (QE) of machine translation output. Marmot contains utilities targeted at quality estimation at the word and phrase level. However, due to its flexibility and modularity, it can also be extended to work at the sentence level. In addition, it can be used as a framework for extracting features and learning models for many common natural language processing tasks. The tool has a set of state-of-the-art features for QE, and new features can easily be added. The tool is open-source and can be downloaded from https://github.com/qe-team/marmot/ |
| Tasks | Machine Translation |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1582/ |
| https://www.aclweb.org/anthology/L16-1582 | |
| PWC | https://paperswithcode.com/paper/marmot-a-toolkit-for-translation-quality |
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Verb sense disambiguation in Machine Translation
| Title | Verb sense disambiguation in Machine Translation |
| Authors | Roman Sudarikov, Ond{\v{r}}ej Du{\v{s}}ek, Martin Holub, Ond{\v{r}}ej Bojar, Vincent Kr{'\i}{\v{z}} |
| Abstract | We describe experiments in Machine Translation using word sense disambiguation (WSD) information. This work focuses on WSD in verbs, based on two different approaches {–} verbal patterns based on corpus pattern analysis and verbal word senses from valency frames. We evaluate several options of using verb senses in the source-language sentences as an additional factor for the Moses statistical machine translation system. Our results show a statistically significant translation quality improvement in terms of the BLEU metric for the valency frames approach, but in manual evaluation, both WSD methods bring improvements. |
| Tasks | Machine Translation, Word Sense Disambiguation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4506/ |
| https://www.aclweb.org/anthology/W16-4506 | |
| PWC | https://paperswithcode.com/paper/verb-sense-disambiguation-in-machine |
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IIP at SemEval-2016 Task 4: Prioritizing Classes in Ensemble Classification for Sentiment Analysis of Tweets
| Title | IIP at SemEval-2016 Task 4: Prioritizing Classes in Ensemble Classification for Sentiment Analysis of Tweets |
| Authors | Jasper Friedrichs |
| Abstract | |
| Tasks | Sentiment Analysis |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1034/ |
| https://www.aclweb.org/anthology/S16-1034 | |
| PWC | https://paperswithcode.com/paper/iip-at-semeval-2016-task-4-prioritizing |
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Chinese Hypernym-Hyponym Extraction from User Generated Categories
| Title | Chinese Hypernym-Hyponym Extraction from User Generated Categories |
| Authors | Chengyu Wang, Xiaofeng He |
| Abstract | Hypernym-hyponym ({}is-a{''}) relations are key components in taxonomies, object hierarchies and knowledge graphs. While there is abundant research on is-a relation extraction in English, it still remains a challenge to identify such relations from Chinese knowledge sources accurately due to the flexibility of language expression. In this paper, we introduce a weakly supervised framework to extract Chinese is-a relations from user generated categories. It employs piecewise linear projection models trained on a Chinese taxonomy and an iterative learning algorithm to update models incrementally. A pattern-based relation selection method is proposed to prevent {}semantic drift{''} in the learning process using bi-criteria optimization. Experimental results illustrate that the proposed approach outperforms state-of-the-art methods. |
| Tasks | Knowledge Graphs, Machine Translation, Named Entity Recognition, Reading Comprehension, Relation Extraction, Word Embeddings |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1128/ |
| https://www.aclweb.org/anthology/C16-1128 | |
| PWC | https://paperswithcode.com/paper/chinese-hypernym-hyponym-extraction-from-user |
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Domain Adaptation and Attention-Based Unknown Word Replacement in Chinese-to-Japanese Neural Machine Translation
| Title | Domain Adaptation and Attention-Based Unknown Word Replacement in Chinese-to-Japanese Neural Machine Translation |
| Authors | Kazuma Hashimoto, Akiko Eriguchi, Yoshimasa Tsuruoka |
| Abstract | This paper describes our UT-KAY system that participated in the Workshop on Asian Translation 2016. Based on an Attention-based Neural Machine Translation (ANMT) model, we build our system by incorporating a domain adaptation method for multiple domains and an attention-based unknown word replacement method. In experiments, we verify that the attention-based unknown word replacement method is effective in improving translation scores in Chinese-to-Japanese machine translation. We further show results of manual analysis on the replaced unknown words. |
| Tasks | Domain Adaptation, Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4605/ |
| https://www.aclweb.org/anthology/W16-4605 | |
| PWC | https://paperswithcode.com/paper/domain-adaptation-and-attention-based-unknown |
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Says Who\ldots? Identification of Expert versus Layman Critics’ Reviews of Documentary Films
| Title | Says Who\ldots? Identification of Expert versus Layman Critics’ Reviews of Documentary Films |
| Authors | Ming Jiang, Jana Diesner |
| Abstract | We extend classic review mining work by building a binary classifier that predicts whether a review of a documentary film was written by an expert or a layman with 90.70{%} accuracy (F1 score), and compare the characteristics of the predicted classes. A variety of standard lexical and syntactic features was used for this supervised learning task. Our results suggest that experts write comparatively lengthier and more detailed reviews that feature more complex grammar and a higher diversity in their vocabulary. Layman reviews are more subjective and contextualized in peoples{'} everyday lives. Our error analysis shows that laymen are about twice as likely to be mistaken as experts than vice versa. We argue that the type of author might be a useful new feature for improving the accuracy of predicting the rating, helpfulness and authenticity of reviews. Finally, the outcomes of this work might help researchers and practitioners in the field of impact assessment to gain a more fine-grained understanding of the perception of different types of media consumers and reviewers of a topic, genre or information product. |
| Tasks | Decision Making, Recommendation Systems |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1200/ |
| https://www.aclweb.org/anthology/C16-1200 | |
| PWC | https://paperswithcode.com/paper/says-whoa-identification-of-expert-versus |
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NLmaps: A Natural Language Interface to Query OpenStreetMap
| Title | NLmaps: A Natural Language Interface to Query OpenStreetMap |
| Authors | Carolin Lawrence, Stefan Riezler |
| Abstract | We present a Natural Language Interface (nlmaps.cl.uni-heidelberg.de) to query OpenStreetMap. Natural language questions about geographical facts are parsed into database queries that can be executed against the OpenStreetMap (OSM) database. After parsing the question, the system provides a text based answer as well as an interactive map with all points of interest and their relevant information marked. Additionally, we provide several options for users to give feedback after a question has been parsed. |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-2002/ |
| https://www.aclweb.org/anthology/C16-2002 | |
| PWC | https://paperswithcode.com/paper/nlmaps-a-natural-language-interface-to-query |
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中文近義詞的偵測與判別(Detection and Discrimination of Chinese Near-synonyms)[In Chinese]
| Title | 中文近義詞的偵測與判別(Detection and Discrimination of Chinese Near-synonyms)[In Chinese] |
| Authors | Shih-Min Li, Ming-Hong Bai, Jian-Cheng Wu, Shu-Ling Huang, Ching-Lung Lin |
| Abstract | |
| Tasks | |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/O16-1030/ |
| https://www.aclweb.org/anthology/O16-1030 | |
| PWC | https://paperswithcode.com/paper/a-ec34eca-eaadetection-and-discrimination-of |
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Faster and Lighter Phrase-based Machine Translation Baseline
| Title | Faster and Lighter Phrase-based Machine Translation Baseline |
| Authors | Liling Tan |
| Abstract | This paper describes the SENSE machine translation system participation in the Third Workshop for Asian Translation (WAT2016). We share our best practices to build a fast and light phrase-based machine translation (PBMT) models that have comparable results to the baseline systems provided by the organizers. As Neural Machine Translation (NMT) overtakes PBMT as the state-of-the-art, deep learning and new MT practitioners might not be familiar with the PBMT paradigm and we hope that this paper will help them build a PBMT baseline system quickly and easily. |
| Tasks | Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4618/ |
| https://www.aclweb.org/anthology/W16-4618 | |
| PWC | https://paperswithcode.com/paper/faster-and-lighter-phrase-based-machine |
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Achieving Accurate Conclusions in Evaluation of Automatic Machine Translation Metrics
| Title | Achieving Accurate Conclusions in Evaluation of Automatic Machine Translation Metrics |
| Authors | Yvette Graham, Qun Liu |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1001/ |
| https://www.aclweb.org/anthology/N16-1001 | |
| PWC | https://paperswithcode.com/paper/achieving-accurate-conclusions-in-evaluation |
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