Paper Group NANR 219
Combining Semantic Annotation of Word Sense & Semantic Roles: A Novel Annotation Scheme for VerbNet Roles on German Language Data. The ADAPT Bilingual Document Alignment system at WMT16. Yes, We Care! Results of the Ethics and Natural Language Processing Surveys. Improving Dependency Parsing Using Sentence Clause Charts. Enlarging Scarce In-domain …
Combining Semantic Annotation of Word Sense & Semantic Roles: A Novel Annotation Scheme for VerbNet Roles on German Language Data
| Title | Combining Semantic Annotation of Word Sense & Semantic Roles: A Novel Annotation Scheme for VerbNet Roles on German Language Data |
| Authors | {'E}va M{'u}jdricza-Maydt, Silvana Hartmann, Iryna Gurevych, Anette Frank |
| Abstract | We present a VerbNet-based annotation scheme for semantic roles that we explore in an annotation study on German language data that combines word sense and semantic role annotation. We reannotate a substantial portion of the SALSA corpus with GermaNet senses and a revised scheme of VerbNet roles. We provide a detailed evaluation of the interaction between sense and role annotation. The resulting corpus will allow us to compare VerbNet role annotation for German to FrameNet and PropBank annotation by mapping to existing role annotations on the SALSA corpus. We publish the annotated corpus and detailed guidelines for the new role annotation scheme. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1484/ |
| https://www.aclweb.org/anthology/L16-1484 | |
| PWC | https://paperswithcode.com/paper/combining-semantic-annotation-of-word-sense |
| Repo | |
| Framework | |
The ADAPT Bilingual Document Alignment system at WMT16
| Title | The ADAPT Bilingual Document Alignment system at WMT16 |
| Authors | Pintu Lohar, Haithem Afli, Chao-Hong Liu, Andy Way |
| Abstract | |
| Tasks | Domain Adaptation, Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2372/ |
| https://www.aclweb.org/anthology/W16-2372 | |
| PWC | https://paperswithcode.com/paper/the-adapt-bilingual-document-alignment-system |
| Repo | |
| Framework | |
Yes, We Care! Results of the Ethics and Natural Language Processing Surveys
| Title | Yes, We Care! Results of the Ethics and Natural Language Processing Surveys |
| Authors | Kar{"e}n Fort, Alain Couillault |
| Abstract | We present here the context and results of two surveys (a French one and an international one) concerning Ethics and NLP, which we designed and conducted between June and September 2015. These surveys follow other actions related to raising concern for ethics in our community, including a Journ{'e}e d{'}{'e}tudes, a workshop and the Ethics and Big Data Charter. The concern for ethics shows to be quite similar in both surveys, despite a few differences which we present and discuss. The surveys also lead to think there is a growing awareness in the field concerning ethical issues, which translates into a willingness to get involved in ethics-related actions, to debate about the topic and to see ethics be included in major conferences themes. We finally discuss the limits of the surveys and the means of action we consider for the future. The raw data from the two surveys are freely available online. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1252/ |
| https://www.aclweb.org/anthology/L16-1252 | |
| PWC | https://paperswithcode.com/paper/yes-we-care-results-of-the-ethics-and-natural |
| Repo | |
| Framework | |
Improving Dependency Parsing Using Sentence Clause Charts
| Title | Improving Dependency Parsing Using Sentence Clause Charts |
| Authors | Vincent Kr{'\i}{\v{z}}, Barbora Hladk{'a} |
| Abstract | |
| Tasks | Dependency Parsing |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-3013/ |
| https://www.aclweb.org/anthology/P16-3013 | |
| PWC | https://paperswithcode.com/paper/improving-dependency-parsing-using-sentence |
| Repo | |
| Framework | |
Enlarging Scarce In-domain English-Croatian Corpus for SMT of MOOCs Using Serbian
| Title | Enlarging Scarce In-domain English-Croatian Corpus for SMT of MOOCs Using Serbian |
| Authors | Maja Popovi{'c}, Kostadin Cholakov, Valia Kordoni, Nikola Ljube{\v{s}}i{'c} |
| Abstract | Massive Open Online Courses have been growing rapidly in size and impact. Yet the language barrier constitutes a major growth impediment in reaching out all people and educating all citizens. A vast majority of educational material is available only in English, and state-of-the-art machine translation systems still have not been tailored for this peculiar genre. In addition, a mere collection of appropriate in-domain training material is a challenging task. In this work, we investigate statistical machine translation of lecture subtitles from English into Croatian, which is morphologically rich and generally weakly supported, especially for the educational domain. We show that results comparable with publicly available systems trained on much larger data can be achieved if a small in-domain training set is used in combination with additional in-domain corpus originating from the closely related Serbian language. |
| Tasks | Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4813/ |
| https://www.aclweb.org/anthology/W16-4813 | |
| PWC | https://paperswithcode.com/paper/enlarging-scarce-in-domain-english-croatian |
| Repo | |
| Framework | |
Boosting for Efficient Model Selection for Syntactic Parsing
| Title | Boosting for Efficient Model Selection for Syntactic Parsing |
| Authors | Rachel Bawden, Beno{^\i}t Crabb{'e} |
| Abstract | We present an efficient model selection method using boosting for transition-based constituency parsing. It is designed for exploring a high-dimensional search space, defined by a large set of feature templates, as for example is typically the case when parsing morphologically rich languages. Our method removes the need to manually define heuristic constraints, which are often imposed in current state-of-the-art selection methods. Our experiments for French show that the method is more efficient and is also capable of producing compact, state-of-the-art models. |
| Tasks | Constituency Parsing, Model Selection |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1001/ |
| https://www.aclweb.org/anthology/C16-1001 | |
| PWC | https://paperswithcode.com/paper/boosting-for-efficient-model-selection-for |
| Repo | |
| Framework | |
Advancing Linguistic Features and Insights by Label-informed Feature Grouping: An Exploration in the Context of Native Language Identification
| Title | Advancing Linguistic Features and Insights by Label-informed Feature Grouping: An Exploration in the Context of Native Language Identification |
| Authors | Serhiy Bykh, Detmar Meurers |
| Abstract | We propose a hierarchical clustering approach designed to group linguistic features for supervised machine learning that is inspired by variationist linguistics. The method makes it possible to abstract away from the individual feature occurrences by grouping features together that behave alike with respect to the target class, thus providing a new, more general perspective on the data. On the one hand, it reduces data sparsity, leading to quantitative performance gains. On the other, it supports the formation and evaluation of hypotheses about individual choices of linguistic structures. We explore the method using features based on verb subcategorization information and evaluate the approach in the context of the Native Language Identification (NLI) task. |
| Tasks | Language Acquisition, Language Identification, Native Language Identification, Text Classification |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1071/ |
| https://www.aclweb.org/anthology/C16-1071 | |
| PWC | https://paperswithcode.com/paper/advancing-linguistic-features-and-insights-by |
| Repo | |
| Framework | |
Anecdote Recognition and Recommendation
| Title | Anecdote Recognition and Recommendation |
| Authors | Wei Song, Ruiji Fu, Lizhen Liu, Hanshi Wang, Ting Liu |
| Abstract | We introduce a novel task Anecdote Recognition and Recommendation. An anecdote is a story with a point revealing account of an individual person. Recommending proper anecdotes can be used as evidence to support argumentative writing or as a clue for further reading. We represent an anecdote as a structured tuple {—} {\textless} person, story, implication {\textgreater}. Anecdote recognition runs on archived argumentative essays. We extract narratives containing events of a person as the anecdote story. More importantly, we uncover the anecdote implication, which reveals the meaning and topic of an anecdote. Our approach depends on discourse role identification. Discourse roles such as thesis, main ideas and support help us locate stories and their implications in essays. The experiments show that informative and interpretable anecdotes can be recognized. These anecdotes are used for anecdote recommendation. The anecdote recommender can recommend proper anecdotes in response to given topics. The anecdote implication contributes most for bridging user interested topics and relevant anecdotes. |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1244/ |
| https://www.aclweb.org/anthology/C16-1244 | |
| PWC | https://paperswithcode.com/paper/anecdote-recognition-and-recommendation |
| Repo | |
| Framework | |
Learning Connective-based Word Representations for Implicit Discourse Relation Identification
| Title | Learning Connective-based Word Representations for Implicit Discourse Relation Identification |
| Authors | Chlo{'e} Braud, Pascal Denis |
| Abstract | |
| Tasks | Feature Engineering, Word Embeddings |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1020/ |
| https://www.aclweb.org/anthology/D16-1020 | |
| PWC | https://paperswithcode.com/paper/learning-connective-based-word |
| Repo | |
| Framework | |
Structured Aspect Extraction
| Title | Structured Aspect Extraction |
| Authors | Omer Gunes, Tim Furche, Giorgio Orsi |
| Abstract | Aspect extraction identifies relevant features from a textual description of an entity, e.g., a phone, and is typically targeted to product descriptions, reviews, and other short texts as an enabling task for, e.g., opinion mining and information retrieval. Current aspect extraction methods mostly focus on aspect terms and often neglect interesting modifiers of the term or embed them in the aspect term without proper distinction. Moreover, flat syntactic structures are often assumed, resulting in inaccurate extractions of complex aspects. This paper studies the problem of structured aspect extraction, a variant of traditional aspect extraction aiming at a fine-grained extraction of complex (i.e., hierarchical) aspects. We propose an unsupervised and scalable method for structured aspect extraction consisting of statistical noun phrase clustering, cPMI-based noun phrase segmentation, and hierarchical pattern induction. Our evaluation shows a substantial improvement over existing methods in terms of both quality and computational efficiency. |
| Tasks | Aspect-Based Sentiment Analysis, Aspect Extraction, Information Retrieval, Opinion Mining, Sentiment Analysis |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1219/ |
| https://www.aclweb.org/anthology/C16-1219 | |
| PWC | https://paperswithcode.com/paper/structured-aspect-extraction |
| Repo | |
| Framework | |
Models and Inference for Prefix-Constrained Machine Translation
| Title | Models and Inference for Prefix-Constrained Machine Translation |
| Authors | Joern Wuebker, Spence Green, John DeNero, Sa{\v{s}}a Hasan, Minh-Thang Luong |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1007/ |
| https://www.aclweb.org/anthology/P16-1007 | |
| PWC | https://paperswithcode.com/paper/models-and-inference-for-prefix-constrained |
| Repo | |
| Framework | |
Infinite Hidden Semi-Markov Modulated Interaction Point Process
| Title | Infinite Hidden Semi-Markov Modulated Interaction Point Process |
| Authors | Matt Zhang, Peng Lin, Peng Lin, Ting Guo, Yang Wang, Yang Wang, Fang Chen |
| Abstract | The correlation between events is ubiquitous and important for temporal events modelling. In many cases, the correlation exists between not only events’ emitted observations, but also their arrival times. State space models (e.g., hidden Markov model) and stochastic interaction point process models (e.g., Hawkes process) have been studied extensively yet separately for the two types of correlations in the past. In this paper, we propose a Bayesian nonparametric approach that considers both types of correlations via unifying and generalizing hidden semi-Markov model and interaction point process model. The proposed approach can simultaneously model both the observations and arrival times of temporal events, and determine the number of latent states from data. A Metropolis-within-particle-Gibbs sampler with ancestor resampling is developed for efficient posterior inference. The approach is tested on both synthetic and real-world data with promising outcomes. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6243-infinite-hidden-semi-markov-modulated-interaction-point-process |
| http://papers.nips.cc/paper/6243-infinite-hidden-semi-markov-modulated-interaction-point-process.pdf | |
| PWC | https://paperswithcode.com/paper/infinite-hidden-semi-markov-modulated |
| Repo | |
| Framework | |
Categorization of Semantic Roles for Dictionary Definitions
| Title | Categorization of Semantic Roles for Dictionary Definitions |
| Authors | Vivian Silva, H, Siegfried schuh, Andr{'e} Freitas |
| Abstract | Understanding the semantic relationships between terms is a fundamental task in natural language processing applications. While structured resources that can express those relationships in a formal way, such as ontologies, are still scarce, a large number of linguistic resources gathering dictionary definitions is becoming available, but understanding the semantic structure of natural language definitions is fundamental to make them useful in semantic interpretation tasks. Based on an analysis of a subset of WordNet{'}s glosses, we propose a set of semantic roles that compose the semantic structure of a dictionary definition, and show how they are related to the definition{'}s syntactic configuration, identifying patterns that can be used in the development of information extraction frameworks and semantic models. |
| Tasks | Question Answering |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-5323/ |
| https://www.aclweb.org/anthology/W16-5323 | |
| PWC | https://paperswithcode.com/paper/categorization-of-semantic-roles-for-1 |
| Repo | |
| Framework | |
A Transition-Based System for Joint Lexical and Syntactic Analysis
| Title | A Transition-Based System for Joint Lexical and Syntactic Analysis |
| Authors | Matthieu Constant, Joakim Nivre |
| Abstract | |
| Tasks | Dependency Parsing |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1016/ |
| https://www.aclweb.org/anthology/P16-1016 | |
| PWC | https://paperswithcode.com/paper/a-transition-based-system-for-joint-lexical |
| Repo | |
| Framework | |
Sentiment Domain Adaptation with Multiple Sources
| Title | Sentiment Domain Adaptation with Multiple Sources |
| Authors | Fangzhao Wu, Yongfeng Huang |
| Abstract | |
| Tasks | Domain Adaptation, Multi-Task Learning, Sentiment Analysis |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1029/ |
| https://www.aclweb.org/anthology/P16-1029 | |
| PWC | https://paperswithcode.com/paper/sentiment-domain-adaptation-with-multiple |
| Repo | |
| Framework | |
