Data-to-Text Generation – Meta-Guide.com

Notes:

Data-to-text generation is a type of natural language processing task that involves generating human-readable text from structured data. This can involve generating descriptions, summaries, reports, or other types of text that convey information about the data in a clear and coherent way.

There are a number of different ways that data-to-text generation can be used. One common use case is to generate reports or summaries of data for use in business or research contexts. For example, a data-to-text system might be used to generate reports about sales data, customer demographics, market trends, or other types of data that are relevant to a particular business or research question.

Another use case for data-to-text generation is to generate descriptions or summaries of data for use in user interfaces or other types of interactive systems. For example, a data-to-text system might be used to generate descriptions of products or services for display on an e-commerce website, or to generate summaries of articles or news stories for presentation in a news feed.

Data-to-text application is a software program or tool that is specifically designed to generate human-readable text from structured data. This could be a standalone program or a feature of a larger system that is used to facilitate the communication and understanding of complex data sets by generating clear and coherent text that conveys the key information and insights contained in the data.
Data-to-text corpora refer to a collection of text or data that is used to train or evaluate a data-to-text system. These corpora typically consist of a large number of examples of data-to-text generation, along with corresponding human-generated text that serves as a reference or benchmark for the system’s performance.
Data-to-text system is a software program or system that is designed to generate human-readable text from structured data. These systems typically use natural language processing and machine learning techniques to analyze the data and generate text that conveys the key information and insights contained in the data in a clear and coherent way.
Data-to-text technology refers to the field of research and development that is focused on developing algorithms, methods, and systems for generating human-readable text from structured data. This technology encompasses a wide range of approaches and techniques, including natural language processing, machine learning, and artificial intelligence, and it is used to facilitate the communication and understanding of complex data sets by generating clear and coherent text that conveys the key information and insights contained in the data.
Textual summarization is the process of generating a summary of a text document or set of documents that captures the key points and main ideas contained in the original text. This can be done manually, by reading and summarizing the text, or it can be done automatically, using natural language processing and machine learning techniques to analyze the text and extract the most important information. Textual summarization is often used to condense large amounts of text into a shorter, more manageable form, or to extract key points and insights from a text for further analysis or interpretation.

References:

Data-to-text generation with content selection and planning
R Puduppully, L Dong, M Lapata – Proceedings of the AAAI Conference on …, 2019 – aaai.org
Recent advances in data-to-text generation have led to the use of large-scale datasets and neural network models which are trained end-to-end, without explicitly modeling what to say and in what order. In this work, we present a neural network architecture which incorporates …

Step-by-step: Separating planning from realization in neural data-to-text generation
A Moryossef, Y Goldberg, I Dagan – arXiv preprint arXiv:1904.03396, 2019 – arxiv.org
Data-to-text generation can be conceptually divided into two parts: ordering and structuring the information (planning), and generating fluent language describing the information (realization). Modern neural generation systems conflate these two steps into a single end-to …

Neural data-to-text generation: A comparison between pipeline and end-to-end architectures
TC Ferreira, C van der Lee, E van Miltenburg… – arXiv preprint arXiv …, 2019 – arxiv.org
Traditionally, most data-to-text applications have been designed using a modular pipeline architecture, in which non-linguistic input data is converted into natural language through several intermediate transformations. In contrast, recent neural models for data-to-text …

Data-to-text generation with entity modeling
R Puduppully, L Dong, M Lapata – arXiv preprint arXiv:1906.03221, 2019 – arxiv.org
Recent approaches to data-to-text generation have shown great promise thanks to the use of large-scale datasets and the application of neural network architectures which are trained end-to-end. These models rely on representation learning to select content appropriately …

Sticking to the facts: Confident decoding for faithful data-to-text generation
R Tian, S Narayan, T Sellam, AP Parikh – arXiv preprint arXiv:1910.08684, 2019 – arxiv.org
Neural conditional text generation systems have achieved significant progress in recent years, showing the ability to produce highly fluent text. However, the inherent lack of controllability in these systems allows them to hallucinate factually incorrect phrases that are …

Improving quality and efficiency in plan-based neural data-to-text generation
A Moryossef, I Dagan, Y Goldberg – arXiv preprint arXiv:1909.09986, 2019 – arxiv.org
We follow the step-by-step approach to neural data-to-text generation we proposed in Moryossef et al (2019), in which the generation process is divided into a text-planning stage followed by a plan-realization stage. We suggest four extensions to that framework:(1) we …

Structural neural encoders for AMR-to-text generation
M Damonte, SB Cohen – arXiv preprint arXiv:1903.11410, 2019 – arxiv.org
Page 1. arXiv:1903.11410v2 [cs.CL] 20 May 2019 Structural Neural Encoders for AMR-to-text Generation Marco Damonte Shay B. Cohen School of Informatics, University of Edinburgh 10 Crichton Street, Edinburgh EH8 9AB, UK m.damonte@sms.ed.ac.uk scohen@inf.ed.ac.uk …

Enhancing amr-to-text generation with dual graph representations
LFR Ribeiro, C Gardent, I Gurevych – arXiv preprint arXiv:1909.00352, 2019 – arxiv.org
Page 1. Enhancing AMR-to-Text Generation with Dual Graph Representations Leonardo FR Ribeiro†, Claire Gardent‡ and Iryna Gurevych† †Research Training Group AIPHES and UKP Lab, Technische Universität Darmstadt …

Hierarchical encoder with auxiliary supervision for neural table-to-text generation: Learning better representation for tables
T Liu, F Luo, Q Xia, S Ma, B Chang, Z Sui – Proceedings of the AAAI …, 2019 – aaai.org
… We achieve the state-of-the-art performance on both automatic and human evaluation metrics. Introduction Data-to-text generation produces understandable texts from some underlying non-linguistic representation of informa- tion (Reiter and Dale 1997; 2000) …

Text generation from knowledge graphs with graph transformers
R Koncel-Kedziorski, D Bekal, Y Luan… – arXiv preprint arXiv …, 2019 – arxiv.org
… Many researchers have sought to address these issues by working with structured inputs. Data-to- text generation models (Konstas and Lapata, 2013; Lebret et al., 2016; Wiseman et al., 2017; Pudup- pully et al., 2019) condition text generation on table-structured inputs …

Enhancing neural data-to-text generation models with external background knowledge
S Chen, J Wang, X Feng, F Jiang, B Qin… – Proceedings of the 2019 …, 2019 – aclweb.org
Recent neural models for data-to-text generation rely on massive parallel pairs of data and text to learn the writing knowledge. They often assume that writing knowledge can be acquired from the training data alone. However, when people are writing, they not only rely …

Key fact as pivot: A two-stage model for low resource table-to-text generation
S Ma, P Yang, T Liu, P Li, J Zhou, X Sun – arXiv preprint arXiv:1908.03067, 2019 – arxiv.org
Page 1. Key Fact as Pivot: A Two-Stage Model for Low Resource Table-to-Text Generation Shuming Ma,1,3 Pengcheng Yang,1,2 Tianyu Liu,1 Peng Li,3 Jie Zhou,3 Xu Sun1,2 1MOE Key Lab of Computational Linguistics, School …

Table-to-text generation with effective hierarchical encoder on three dimensions (row, column and time)
H Gong, X Feng, B Qin, T Liu – arXiv preprint arXiv:1909.02304, 2019 – arxiv.org
Page 1. Table-to-Text Generation with Effective Hierarchical Encoder on Three Dimensions (Row, Column and Time) Heng Gong, Xiaocheng Feng, Bing Qin?, Ting Liu Harbin Institute of Technology, China 1hgong, xcfeng, qinb, tliul@ir.hit.edu.cn Abstract …

Viggo: A video game corpus for data-to-text generation in open-domain conversation
J Juraska, KK Bowden, M Walker – arXiv preprint arXiv:1910.12129, 2019 – arxiv.org
The uptake of deep learning in natural language generation (NLG) led to the release of both small and relatively large parallel corpora for training neural models. The existing data-to-text datasets are, however, aimed at task-oriented dialogue systems, and often thus limited …

Data-to-text generation with attention recurrent unit
H Wang, W Zhang, Y Zhu, Z Bai – 2019 International Joint …, 2019 – ieeexplore.ieee.org
Recurrent Neural Networks (RNNs) have shown promising results in many text generation tasks with their ability in modeling complex data distribution. However, the text generation model in their encoder or decoder RNNs still can not use the context efficiently. In this paper …

Learning to select, track, and generate for data-to-text
H Iso, Y Uehara, T Ishigaki, H Noji, E Aramaki… – arXiv preprint arXiv …, 2019 – arxiv.org
… Abstract We propose a data-to-text generation model with two modules, one for tracking and the other for text generation. Our tracking mod- ule selects and keeps track of salient infor- mation and memorizes which record has been mentioned …

Moverscore: Text generation evaluating with contextualized embeddings and earth mover distance
W Zhao, M Peyrard, F Liu, Y Gao, CM Meyer… – arXiv preprint arXiv …, 2019 – arxiv.org
… using word-based metrics (Post, 2018). Data-to-text Generation BLEU can be poorly suited to evaluating data-to-text systems such as dialogue response generation and image caption- ing. These systems are designed to generate …

Text generation with exemplar-based adaptive decoding
H Peng, AP Parikh, M Faruqui, B Dhingra… – arXiv preprint arXiv …, 2019 – arxiv.org
… We evaluate the proposed model on abstractive text sum- marization and data-to-text generation. Em- pirical results show that this model achieves strong performance and outperforms compara- ble baselines. 1 Introduction …

Creating a corpus for Russian data-to-text generation using neural machine translation and post-editing
A Shimorina, E Khasanova, C Gardent – … of the 7th Workshop on Balto …, 2019 – aclweb.org
In this paper, we propose an approach for semi-automatically creating a data-to-text (D2T) corpus for Russian that can be used to learn a D2T natural language generation model. An error analysis of the output of an English-to-Russian neural machine translation system …

Select and attend: Towards controllable content selection in text generation
X Shen, J Suzuki, K Inui, H Su, D Klakow… – arXiv preprint arXiv …, 2019 – arxiv.org
… 5.1 Tasks and Setup We test content-selection models on the headline and data-to-text generation task. Both tasks share the same framework with the only difference of source-side encoders. Headline Generation: We use English Giga- word preprocessed by Rush et al …

Enhanced Transformer Model for Data-to-Text Generation
G Li, JM Crego, J Senellart – Proceedings of the 3rd Workshop on Neural …, 2019 – aclweb.org
Neural models have recently shown significant progress on data-to-text generation tasks in which descriptive texts are generated conditioned on database records. In this work, we present a new Transformer-based data-to-text generation model which learns content …

Copy mechanism and tailored training for character-based data-to-text generation
M Roberti, G Bonetta, R Cancelliere… – … European Conference on …, 2019 – Springer
In the last few years, many different methods have been focusing on using deep recurrent neural networks for natural language generation. The most widely used sequence-to-sequence neural methods are word-based: as such, they need a pre-processing step called …

Template-free Data-to-Text Generation of Finnish Sports News
J Kanerva, S Rönnqvist, R Kekki, T Salakoski… – arXiv preprint arXiv …, 2019 – arxiv.org
News articles such as sports game reports are often thought to closely follow the underlying game statistics, but in practice they contain a notable amount of background knowledge, interpretation, insight into the game, and quotes that are not present in the official statistics …

Table-to-Text Generation via Row-Aware Hierarchical Encoder
H Gong, X Feng, B Qin, T Liu – China National Conference on Chinese …, 2019 – Springer
… 2 Background. 2.1 Task Definition. We model the document-scale data-to-text generation task in an end-to-end fashion. Statistics STAT consists of multiple records \(\{r_{1,1},… r_{i, j}…, r_{R,C}\}\) where R is the number of rows and C is the number of columns …

An Encoder with non-Sequential Dependency for Neural Data-to-Text Generation
F Nie, J Wang, R Pan, CY Lin – … of the 12th International Conference on …, 2019 – aclweb.org
Data-to-text generation aims to generate descriptions given a structured input data (ie, a table with multiple records). Existing neural methods for encoding input data can be divided into two categories: a) pooling based encoders which ignore dependencies between input …

Two-level model for table-to-text generation
J Cao, J Gong, P Zhang – … of the 2019 International Symposium on …, 2019 – dl.acm.org
… neural network 1. INTRODUCTION Table-to-text generation belongs to data-to-text generation as an important task for text generation from structured data, and it is also called table summarization by some researchers. The task …

Long and diverse text generation with planning-based hierarchical variational model
Z Shao, M Huang, J Wen, W Xu, X Zhu – arXiv preprint arXiv:1908.06605, 2019 – arxiv.org
… 1 Introduction Data-to-text generation is to generate natural lan- guage texts from structured data (Gatt and Krah- mer, 2018), which has a wide range of applications (for weather forecast, game report, product de- scription, advertising document, etc.) …

Sentence-level content planning and style specification for neural text generation
X Hua, L Wang – arXiv preprint arXiv:1909.00734, 2019 – arxiv.org
Page 1. Sentence-Level Content Planning and Style Specification for Neural Text Generation Xinyu Hua and Lu Wang Khoury College of Computer Sciences Northeastern University Boston, MA 02115 hua.x@husky.neu.edu luwang@ccs.neu.edu Abstract …

Table-to-Text Natural Language Generation with Unseen Schemas
T Liu, W Wei, WY Wang – arXiv preprint arXiv:1911.03601, 2019 – arxiv.org
… to seen ones. • We construct a benchmark dataset for this new task and demonstrate the effectiveness and capability of our method to deal with unseen table schemas. 2 Related Work 2.1 Data-to-Text Generation Data-to-text …

Copy mechanism and tailored training for character-based data-to-text generation
R Cancelliere, P Gallinari – arXiv preprint arXiv:1904.11838, 2019 – researchgate.net
In the last few years, many different methods have been focusing on using deep recurrent neural networks for natural language generation. The most widely used sequence-to-sequence neural methods are word-based: as such, they need a pre-processing step called …

Emotional Text Generation Based on Cross-Domain Sentiment Transfer
R Zhang, Z Wang, K Yin, Z Huang – IEEE Access, 2019 – ieeexplore.ieee.org
Page 1. Received July 2, 2019, accepted July 16, 2019, date of publication July 25, 2019, date of current version August 8, 2019. Digital Object Identifier 10.1109/ACCESS.2019.2931036 Emotional Text Generation Based on Cross-Domain Sentiment Transfer …

Selecting, planning, and rewriting: A modular approach for data-to-document generation and translation
LM Werlen, M Marone, H Hassan – Proceedings of the 3rd Workshop on …, 2019 – aclweb.org
… 1 Introduction Data-to-text generation focuses on generating nat- ural text from structured inputs such as table records. Traditional data-to-text systems used a pipelined approach for data selection followed by planning and text generation …

A hybrid model for globally coherent story generation
F Zhai, V Demberg, P Shkadzko, W Shi… – Proceedings of the …, 2019 – aclweb.org
Page 1. Proceedings of the Second Storytelling Workshop, pages 34–45 Florence, Italy, August 1, 2019. c 2019 Association for Computational Linguistics 34 A Hybrid Model for Globally Coherent Story Generation Zhai Fangzhou …

A Personalized Data-to-Text Support Tool for Cancer Patients
S Hommes, C van der Lee, F Clouth… – Proceedings of the 12th …, 2019 – aclweb.org
… We highlight the possibilities of NLG for personalization, dis- cuss ethical implications and also present the outcomes of a first evaluation with clinicians. 1 Introduction Data-to-text generation systems are increasingly used in the health domain (Pauws et al., 2019) …

c-TextGen: Conditional Text Generation for Harmonious Human-Machine Interaction
B Guo, H Wang, Y Ding, S Hao, Y Sun, Z Yu – arXiv preprint arXiv …, 2019 – arxiv.org
… variety of tasks. According to di erent data sources, text generation can be divided into data-to-text, text-to-text, and image-to-text generation. News generation is a typical application of data-to-text generation. ere was an earthquake …

Paraphrase generation with latent bag of words
Y Fu, Y Feng, JP Cunningham – Advances in Neural Information …, 2019 – papers.nips.cc
… 2018. URL https://github. com/FranxYao/Deep-Generative-Models-for-Natural-Language- Processing. [13] Sebastian Gehrmann, Falcon Z. Dai, Henry Elder, and Alexander M. Rush. End-to-end content and plan selection for data-to-text generation. In INLG, 2018 …

A Closer Look at Recent Results of Verb Selection for Data-to-Text NLG
G Chen, JG Yao – Proceedings of the 12th International Conference on …, 2019 – aclweb.org
… magnitude, of a percentage change. Likewise, an automatic natural language generation systems for data-to-text generation un- der similar scenarios should also properly select verbs as well. In earlier systems, neutral verbs …

Improving Language Generation from Feature-Rich Tree-Structured Data with Relational Graph Convolutional Encoders
X Hong, E Chang, V Demberg – Proceedings of the 2nd Workshop on …, 2019 – aclweb.org
… improvement. Two of such changes are the copy mechanism and coverage Page 5. 79 attention. The copy mechanism was shown to be beneficial in numerous similar tasks such as data-to-text generation (Li and Wan, 2018). With …

Remodeling Numerical Representation for Text Generation on Small Corpus: A Syntactical Analysis
A Tan, HN Goh, LK Wong – Proceedings of the 2019 2nd International …, 2019 – dl.acm.org
… Lai-Kuan Wong Faculty of Com. & Informatics Multimedia University 63100 Cyberjaya, Malaysia lkwong@mmu.edu.my ABSTRACT Data-to-text generation aims to generate natural language descriptions from non-linguistic data …

Semi-Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models
R Qader, F Portet, C Labbé – arXiv preprint arXiv:1910.03484, 2019 – arxiv.org
Page 1. arXiv:1910.03484v1 [cs.CL] 29 Sep 2019 Semi-Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models Raheel Qader1 François Portet2 Cyril Labbé2 Univ …

Unsupervised Text Generation from Structured Data
M Schmitt, S Sharifzadeh, V Tresp… – arXiv preprint arXiv …, 2019 – arxiv.org
… extraction). Our contributions are: (1) We propose a joint model for data to text generation and open informa- tion extraction (Niklaus et al., 2018). (2) We obtain first results in a fully unsupervised setting for the above tasks. (3 …

Selected Challenges in Grammar-Based Text Generation from the Semantic Web
S Mille – Artificial Intelligence, 2019 – Springer
… http://www.aclweb.org/anthology/S17-2158. 25. Mille, S., Wanner, L.: Towards large-coverage detailed lexical resources for data-to-text generation. In: Proceedings of the First International Workshop on Data-to-text Generation, Edinburgh, Scotland (2015)Google Scholar. 26 …

Neural data-to-text generation: A comparison between pipeline and end-to-end architectures
T Castro Ferreira, C van der Lee, E van Miltenburg… – arXiv, 2019 – ui.adsabs.harvard.edu
Traditionally, most data-to-text applications have been designed using a modular pipeline architecture, in which non-linguistic input data is converted into natural language through several intermediate transformations. In contrast, recent neural models for data-to-text …

The curious case of neural text degeneration
A Holtzman, J Buys, L Du, M Forbes, Y Choi – arXiv preprint arXiv …, 2019 – arxiv.org
… input. Example applications include machine translation (Bahdanau et al., 2015), data-to-text generation (Wiseman et al., 2017), and summarization (Nallapati et al., 2016). We refer to these tasks as directed generation. Typically …

Beyond Word for Word: Fact Guided Training for Neural Data-to-Document Generation
F Nie, H Chen, J Wang, R Pan, CY Lin – CCF International Conference on …, 2019 – Springer
… Abstract. Recent end-to-end encoder-decoder neural models for data-to-text generation can produce fluent and seemingly informative texts despite these models disregard the traditional content selection and surface realization architecture …

Storytelling from structured data and knowledge graphs: An NLG perspective
A Mishra, A Laha, K Sankaranarayanan… – Proceedings of the 57th …, 2019 – aclweb.org
… However, these approaches are data-hungry and perform miserably on datasets from unseen domains (Gardent et al., 2017). Real- izing this, some of the very recent works in data- to-text generation such as Wiseman et al …

Encode, tag, realize: High-precision text editing
E Malmi, S Krause, S Rothe, D Mirylenka… – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. Encode, Tag, Realize: High-Precision Text Editing Eric Malmi Google Research emalmi@google.com Sebastian Krause Google Research bastik@google. com Sascha Rothe Google Research rothe@google.com Daniil …

Storyboarding of recipes: grounded contextual generation
KR Chandu, E Nyberg, A Black – 2019 – openreview.net
… Association for Computational Linguistics, 2002. Ratish Puduppully, Li Dong, and Mirella Lapata. Data-to-text generation with content selection and planning. arXiv preprint arXiv:1809.00582, 2018. Amaia Salvador, Michal Drozdzal, Xavier Giro-i Nieto, and Adriana Romero …

Generating Text from Anonymised Structures
E Colin, C Gardent – Proceedings of the 12th International Conference …, 2019 – aclweb.org
… 1 Introduction Surface realisation (SR), the ability to generate text from meaning representations (MR), is a key component of data-to-text generation. In this pa- per, we focus on surface realisation for French. We make two contributions …

A Semi-Supervised Approach for Low-Resourced Text Generation
H Zang, X Wan – arXiv preprint arXiv:1906.00584, 2019 – arxiv.org
… 2017; Lample et al., 2017). 4 Experiments 4.1 Tasks and Datasets 4.1.1 Data-to-Text Generation on WebNLG The WebNLG dataset is a corpus designed for data-to-text generation (Gardent et al., 2017). And there was an open …

On Improving Text Generation Via Integrating Text Coherence
L Ai, B Gao, J Zheng, M Gao – 2019 IEEE 6th International …, 2019 – ieeexplore.ieee.org
… In the past few years, automatic text generation technology has developed rapidly, which can be divided into text-to-text generation [3-12], meaning-to-text generation [13], data-to-text generation [14-16], and image-to-text generation [17] according to the data types of input …

A Hybrid Model for Globally Coherent Story Generation
Z Fangzhou, V Demberg, P Shkadzko, W Shi… – ACL 2019, 2019 – aclweb.org
… In Proceedings of the First Workshop on Storytelling, pages 43–49. Ratish Puduppully, Li Dong, and Mirella Lapata. 2018. Data-to-text generation with content selection and planning. arXiv preprint arXiv: 1809.00582. Christopher Purdy, Xinyu Wang, Larry He, and Mark Riedl …

Interactive map reports summarizing bivariate geographic data
S Latif, F Beck – Visual Informatics, 2019 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Proceedings of the 12th International Conference on Natural Language Generation
K van Deemter, C Lin, H Takamura – Proceedings of the 12th …, 2019 – aclweb.org
… 136 An Encoder with non-Sequential Dependency for Neural Data-to-Text Generation Feng Nie, Jinpeng Wang, Rong Pan and Chin-Yew Lin . . . . . 141 …

Storytelling from Structured Data and Knowledge Graphs An NLG Perspective
AMALK Sankaranarayanan, PJS Krishnan – ACL 2019, 2019 – aclweb.org
… domains (Gardent et al., 2017). Real- izing this, some of the very recent works in data- to-text generation such as Wiseman et al.(2018) have focused on learning templates from corpora for neural NLG. Evaluation Methods for NLG …

Toward Controllable Text Content Manipulation
S Lin, W Wang, Z Hu, Z Yang, X Liang, H Shi, F Xu… – 2019 – openreview.net
… The problem combines the characteristics of data-to-text generation and style transfer, and is challenging to minimally yet effectively manipulate the text (by rewriting/adding/ deleting text portions) to ensure fidelity to the structured con- tent …

Recurrent Convolution Attention Model (RCAM) for Text Generation based on Title
Y Jianglin, G Zhigang, C Gang – Journal of Physics: Conference …, 2019 – iopscience.iop.org
… Therefore, it has more significance for NLP research. 1. Introduction Both text-to-text generation and data-to-text generation are instances of Natural Language Generation (NLG) [1]. In this paper, we research more on text to text, so called text generation …

A Novel Task-Oriented Text Corpus in Silent Speech Recognition and its Natural Language Generation Construction Method
D Cao, D Zhang, HB Chen – Proceedings of the 2019 3rd International …, 2019 – dl.acm.org
… In the process of construction, we propose a task-oriented hybrid construction method based on natural language generation (NLG) algorithm. The algorithm focuses on the strategy of data-to-text generation, and has two advantages including linguistic quality and high diversity …

Towards comprehensive description generation from factual attribute-value tables
T Liu, F Luo, P Yang, W Wu, B Chang… – Proceedings of the 57th …, 2019 – aclweb.org
Page 1. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5985–5996 Florence, Italy, July 28 – August 2, 2019. c 2019 Association for Computational Linguistics 5985 Towards Comprehensive …

Set to Ordered Text: Generating Discharge Instructions from Medical Billing Codes
LJ Kurisinkel, N Chen – Proceedings of the 2019 Conference on …, 2019 – aclweb.org
Page 1. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, pages 6165–6175, Hong Kong, China, November 3–7, 2019 …

Decomposable neural paraphrase generation
Z Li, X Jiang, L Shang, Q Liu – arXiv preprint arXiv:1906.09741, 2019 – arxiv.org
Page 1. Decomposable Neural Paraphrase Generation Zichao Li, Xin Jiang, Lifeng Shang, Qun Liu Huawei Noah’s Ark Lab {li.zichao, jiang.xin, shang.lifeng, qun.liu}@huawei.com Abstract Paraphrasing exists at different granularity …

Neural Generation for Czech: Data and Baselines
O Dušek, F Jur?í?ek – arXiv preprint arXiv:1910.05298, 2019 – arxiv.org
Page 1. In Proceedings of INLG, Tokyo, Japan, October 2019. Neural Generation for Czech: Data and Baselines Ondrej Dušek and Filip Jurc?cek Charles University, Faculty of Mathematics and Physics Institute of Formal and …

Cosql: A conversational text-to-sql challenge towards cross-domain natural language interfaces to databases
T Yu, R Zhang, HY Er, S Li, E Xue, B Pang… – arXiv preprint arXiv …, 2019 – arxiv.org
… questions. Data-to-Text generation Response generation in CoSQL takes a structured SQL query and its corresponding result table to generate an NL de- scription of the system’s interpretation of the user request. Compared …

Going GREAN: A Novel Framework and Evaluation Metric for the Graph-to-Text Generation Task
O Sheffer, O Castel, R Landau – cs.tau.ac.il
… translation. arXiv preprint arXiv:1508.04025, 2015. Marcheggiani, D. and Perez-Beltrachini, L. Deep graph con- volutional encoders for structured data to text generation. arXiv preprint arXiv:1810.09995, 2018. Marcheggiani …

Paperrobot: Incremental draft generation of scientific ideas
Q Wang, L Huang, Z Jiang, K Knight, H Ji… – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. PaperRobot: Incremental Draft Generation of Scientific Ideas Qingyun Wang1, Lifu Huang1, Zhiying Jiang1, Kevin Knight2, Heng Ji1,3, Mohit Bansal4, Yi Luan5 1 Rensselaer Polytechnic Institute 2 DiDi Labs 3 University …

Generating live soccer-match commentary from play data
Y Taniguchi, Y Feng, H Takamura… – Proceedings of the AAAI …, 2019 – aaai.org
… The task is regarded as a data-to-text generation task, but has characteristics that text is only partially aligned to Copyright c 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved …

Findings of the third workshop on neural generation and translation
H Hayashi, Y Oda, A Birch, I Konstas, A Finch… – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. Findings of the Third Workshop on Neural Generation and Translation Hiroaki Hayashi?, Yusuke Oda?, Alexandra Birch?, Ioannis Konstas?, Andrew Finch?, Minh-Thang Luong?, Graham Neubig?, Katsuhito Sudoh …

How to Tell Real from Fake: research on text generation and linguistic feature in text classification
J Zhang – 2019 – courses.cecs.anu.edu.au
… Generating data into text applies to this definition. Wan et al. extended this concept to include text-to-text generation, data-to-text generation, and image-to-text generation [21]. Text generation is an important research direction in the field of natural language processing …

Toward unsupervised text content manipulation
W Wang, Z Hu, Z Yang, H Shi, F Xu, E Xing – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. Toward Unsupervised Text Content Manipulation Wentao Wang?, Zhiting Hu?, Zichao Yang, HaoranShi, FrankXu, EricXing (*equal contribution) Carnegie Mellon University, Petuum Inc. {wwt.cpp,zhitinghu,yangtze2301,haoranshi97}@gmail.com eric.xing@petuum.com …

Learning Semantic Correspondences from Noisy Data-text Pairs by Local-to-Global Alignments
F Nie, J Wang, R Pan, CY Lin – 2019 – openreview.net
… ALIGNMENTS Anonymous authors Paper under double-blind review ABSTRACT Learning semantic correspondences between the structured data (eg, slot-value pairs) and associated texts is a core problem for many downstream NLP applica- tions, eg, data-to-text generation …

University of Edinburgh’s submission to the Document-level Generation and Translation Shared Task
R Puduppully, J Mallinson, M Lapata – … of the 3rd Workshop on Neural …, 2019 – aclweb.org
… ACL. Ratish Puduppully, Li Dong, and Mirella Lapata. 2019. Data-to-text generation with content selection and planning. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 33, pages 6908– 6915. Rico Sennrich, Barry Haddow, and Alexandra Birch. 2015a …

Difficulty-controllable multi-hop question generation from knowledge graphs
V Kumar, Y Hua, G Ramakrishnan, G Qi, L Gao… – International Semantic …, 2019 – Springer
Knowledge graphs have become ubiquitous data sources and their utility has been amplified by the research on ability to answer carefully crafted questions over knowledge graphs. We investigate the…

Naver Labs Europe’s Systems for the Document-Level Generation and Translation Task at WNGT 2019
F Saleh, A Bérard, I Calapodescu… – arXiv preprint arXiv …, 2019 – arxiv.org
… The two aspects which are mostly addressed in data-to-text generation techniques are identi- fying the most important information from input data, and verbalizing data as a coherent docu- ment: “What to talk about and how?” (Mei et al., 2016) …

A Hierarchical Attention Based Seq2Seq Model for Chinese Lyrics Generation
H Fan, J Wang, B Zhuang, S Wang, J Xiao – Pacific Rim International …, 2019 – Springer
… 5. 2 Related Work. NLG is an essential part of natural language processing (NLP). According to the modality of input, there exist text-to-text generation, meaning-to-text generation, data-to-text generation, image-to-text generation etc …

Financial News Generation Based on Artificial Intelligence Technology
S Cao, Y Yue – 2019 2nd International Conference on Safety …, 2019 – ieeexplore.ieee.org
… In recent years, with the development of research on data to text generation, researchers have introduced neural network methods into this field, mainly building models based on circular neural network, and have made good research progress[1]. It can be seen that the core …

Tool for Journalists to Edit the Text Generation Logic of an Automated Journalist
K Puro – 2019 – utupub.fi
Page 1. Tool for Journalists to Edit the Text Generation Logic of an Automated Journalist Master of Science Thesis University of Turku Department of Future Technologies Software Engineering 2019 Kyösti Puro The originality …

Natural Language Generation for Operations and Maintenance in Wind Turbines
J Chatterjee, N Dethlefs – pdfs.semanticscholar.org
… fix faults. We present a data-to-text generation system using transformers to produce event descriptions from SCADA data capturing the operational status of turbines and proposing maintenance strategies. Experiments show …

Introduction to natural language processing
J Eisenstein – 2019 – books.google.com
… 399 Machine Translation 405 18.1 Machine Translation as a Task 405 18.2 Statistical Machine Translation 410 18.3 Neural Machine Translation 415 18.4 Decoding 423 18.5 Training toward the Evaluation Metric 424 Text Generation 431 19.1 Data-to-Text Generation 431 19.2 …

Learning to Predict Explainable Plots for Neural Story Generation
G Chen, Y Liu, H Luan, M Zhang, Q Liu… – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. Learning to Predict Explainable Plots for Neural Story Generation Gang Chen†, Yang Liu†‡, Huanbo Luan†, Meng Zhang#, Qun Liu# and Maosong Sun† †Institute for Artificial Intelligence State Key Laboratory of Intelligent …

Proceedings of the 3rd Workshop on Neural Generation and Translation
A Birch, A Finch, H Hayashi, I Konstas… – Proceedings of the 3rd …, 2019 – aclweb.org
… 138 Enhanced Transformer Model for Data-to-Text Generation Li GONG, Josep Crego and Jean Senellart . . . . . 148 Generalization …

Generating personalized recipes from historical user preferences
BP Majumder, S Li, J Ni, J McAuley – arXiv preprint arXiv:1909.00105, 2019 – arxiv.org
… Our work combines two important tasks from natural language processing and recommender systems: data-to-text generation (Gatt and Krah- mer, 2018) and personalized recommendation * denotes equal contribution (Rashid et al., 2002) …

Best practices for the human evaluation of automatically generated text
C Van Der Lee, A Gatt, E Van Miltenburg… – Proceedings of the 12th …, 2019 – aclweb.org
Page 1. Proceedings of The 12th International Conference on Natural Language Generation, pages 355–368, Tokyo, Japan, 28 Oct – 1 Nov, 2019. c 2019 Association for Computational Linguistics 355 Best practices for the human evaluation of automatically generated text …

Teaching FORGe to Verbalize DBpedia Properties in Spanish
S Mille, S Dasiopoulou, B Fisas, L Wanner – Proceedings of the 12th …, 2019 – aclweb.org
Page 1. Proceedings of The 12th International Conference on Natural Language Generation, pages 473–483, Tokyo, Japan, 28 Oct – 1 Nov, 2019. c 2019 Association for Computational Linguistics 473 Teaching FORGe to Verbalize DBpedia Properties in Spanish …

Automatic Quality Estimation for Natural Language Generation: Ranting (Jointly Rating and Ranking)
O Dušek, K Sevegnani, I Konstas, V Rieser – arXiv preprint arXiv …, 2019 – arxiv.org
… Sebastian Gehrmann, Falcon Z. Dai, Henry Elder, and Alexander M. Rush. 2018. End-to-End Content and Plan Selection for Data-to-Text Generation. In Pro- ceedings of the International Conference on Natural Language Generation, Tilburg, The Netherlands …

A library for automatic natural language generation of spanish texts
S García-Méndez, M Fernández-Gavilanes… – Expert Systems with …, 2019 – Elsevier
… Most data-to-text generation methods rely on predefined templates to automatically transform data into text by filling gaps in predefined text templates, which has applications in reportage of weather, traffic, sports, health, etc …

A Tree-to-Sequence Model for Neural NLG in Task-Oriented Dialog
J Rao, K Upasani, A Balakrishnan, M White… – Proceedings of the 12th …, 2019 – aclweb.org
… AAAI. Diego Marcheggiani and Laura Perez-Beltrachini. 2018. Deep graph convolutional encoders for struc- tured data to text generation. In Proceedings of the 11th International Conference on Natural Lan- guage Generation, pages 1–9, Tilburg University, The Netherlands …

AUTOMATED CRICKET NEWS GENERATION IN SRI LANKAN STYLE USING NATURAL LANGUAGE GENERATION
DY Gunasiri, KL Jayaratne – European Journal of Computer …, 2019 – researchgate.net
… California. This was reported within 3 minutes and it was automatically generated by a ‘robot journalist’ which converts the input parameters to a pre-defined template [12]. This was a data-to- text generation system. Automated …

Proceedings of the 1st Workshop on Discourse Structure in Neural NLG
A Balakrishnan, V Demberg, C Khatri… – Proceedings of the 1st …, 2019 – aclweb.org
… In contrast, influenced by the phenomenon of deep learning, recent neural models for data-to-text generation have been proposed as end-to-end approaches, where the non-linguistic input is rendered in natural language with much less ex- plicit intermediate representations in …

Context computing for internet of things
HJT Manaligod, MJS Diño, S Ghose, J Han – 2019 – Springer
… effects on logistics-information quality. The seventh paper by Jang et al. (2019) suggests narrative, context-based, data-to-text generation in natural language generation models of ambient intelligence. The composition of the data …

A Comparison of Data-Driven and Template-Based Approaches to Natural Language Generation
J Dunn – projects.cs.uct.ac.za
… driven system. KEYWORDS Natural Language Generation, NLG, Data-to-text Generation, Ma- chine Learning, Data-driven Natural Language Generation, Template- based Natural Language Generation 1 INTRODUCTION …

An analysis of templates for generating text for use in comparing with data-driven models
M Poulter – projects.cs.uct.ac.za
… Keywords natural language generation; data-to-text generation; template- based models; text analysis 1. INTRODUCTION With the rise in popularity of data-to-text generation in recent years, so too has this field of study grown and developed …

Story Generation from Smart Phone Data: A script approach
TK Nguyen – 2019 – tel.archives-ouvertes.fr
… situations of everyday life. This work is described in Chapter 6. 1.3 Thesis Outline Chapter 2 gives a short overview of the state-of-the-art on both data-to-text generation and script learning and generation. Then, it presents human activity recognition (HAR) …

Stylistic Control for Neural Natural Language Generation
S Oraby – 2019 – escholarship.org
Page 1. UC Santa Cruz UC Santa Cruz Electronic Theses and Dissertations Title Stylistic Control for Neural Natural Language Generation Permalink https://escholarship.org/uc/item/54p9r87q Author Oraby, Shereen Publication Date 2019 Peer reviewed|Thesis/dissertation …

Automated Chess Commentator Powered by Neural Chess Engine
H Zang, Z Yu, X Wan – arXiv preprint arXiv:1909.10413, 2019 – arxiv.org
… language space. And to realize this, we deploy multi-task learning (Collobert and Weston, 2008; Sanh et al., 2018) in our proposed models. Data-to-text generation is a popular track in NLG researches. Recent researches are …

Constructing Statistical Data-driven Natural Language Generation Systems for Comparison Against Template-based Systems
J Dunn – projects.cs.uct.ac.za
… 1101. [8] Amit Moryossef, Yoav Goldberg, and Ido Dagan. 2019. Step-by-Step: Sepa- rating Planning from Realization in Neural Data-to-Text Generation. CoRR abs/1904.03396 (2019). [9] Jekaterina Novikova, Ondrej Dusek, Amanda Cercas Curry, and Verena Rieser. 2017 …

SYSTRAN@ WNGT 2019: DGT Task
G Li, JM Crego, J Senellart – Proceedings of the 3rd Workshop on Neural …, 2019 – aclweb.org
… 1 Introduction Data-to-text generation is an important task in natural language generation (NLG). It refers to the task of automatically producing a descriptive text from non-linguistic structured data (tables, database records, spreadsheets, etc.) …

Captioning Events in Tourist Spots by Neural Language Generation
M Nguyen – ahcweb01.naist.jp
… more natu- rally, removes the dependency on the predefined rules. Neural-based models have also been successfully applied to various data-to-text generation tasks. More recently, there has been some work on neural-based …

Few-shot nlg with pre-trained language model
Z Chen, H Eavani, W Chen, Y Liu, WY Wang – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. Few-Shot NLG with Pre-Trained Language Model Zhiyu Chen1, Harini Eavani2, Wenhu Chen1, Yinyin Liu2, William Yang Wang1 University of California, Santa Barbara Intel AI Lab {zhiyuchen, wenhuchen, william}@cs.ucsb.edu, {harini.eavani, yinyin.liu}@intel.com …

Barack’s Wife Hillary: Using Knowledge-Graphs for Fact-Aware Language Modeling
RL Logan IV, NF Liu, ME Peters, M Gardner… – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. Barack’s Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling Robert L. Logan IV? Nelson F. Liu†§ Matthew E. Peters§ Matt Gardner§ Sameer Singh? ? University of California, Irvine, CA, USA …

A simple recipe towards reducing hallucination in neural surface realisation
F Nie, JG Yao, J Wang, R Pan, CY Lin – … of the 57th Annual Meeting of …, 2019 – aclweb.org
Page 1. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2673–2679 Florence, Italy, July 28 – August 2, 2019. c 2019 Association for Computational Linguistics 2673 A Simple Recipe …

Fine-Grained Control of Sentence Segmentation and Entity Positioning in Neural NLG
K Mehta, R Qader, C Labbe, F Portet – 2019 – hal.archives-ouvertes.fr
… arXiv preprint arXiv:1509.00838. Amit Moryossef, Yoav Goldberg, and Ido Dagan. 2019. Step-by-step: Separating planning from realization in neural data-to-text generation. arXiv preprint arXiv:1904.03396. Neha Nayak, Dilek Hakkani-Tür, Marilyn A Walker, and Larry P Heck …

Designing a symbolic intermediate representation for neural surface realization
H Elder, J Foster, J Barry, A O’Connor – arXiv preprint arXiv:1905.10486, 2019 – arxiv.org
… neural NLG (Dušek and Jurcicek, 2016; Daniele et al., 2017; Puduppully et al., 2018; Hajdik et al., 2019; Moryossef et al., 2019), and inspired by more traditional pipeline data-to-text generation (Reiter and Dale, 2000; Gatt and Krahmer, 2018), we present a system which splits …

A Corpus Complexity Analyzer for NLP Applications
T Gupta, B Srivastava, A Bauer – researchgate.net
… Data-to-text gen- eration with entity modeling. Natural Language Processing with Python, OReilly. Puduppully, R.; Dong, L.; and Lapata, M. 2019. Data-to-text generation with entity modeling. ACL. van der Maaten, L., and Hinton, G. 2008. Visualizing data using t-SNE …

PoMo: Generating Entity-Specific Post-Modifiers in Context
JS Kang, RL Logan IV, Z Chu, Y Chen, D Dua… – arXiv preprint arXiv …, 2019 – arxiv.org
… Post-modifier generation is a contextual data-to- text generation problem, where the data is the set of known facts about the target entity, and the text to be generated is a post-modifier that is relevant to the rest of the information conveyed in the text. Figure 1 shows an example …

Generating summaries with topic templates and structured convolutional decoders
L Perez-Beltrachini, Y Liu, M Lapata – arXiv preprint arXiv:1906.04687, 2019 – arxiv.org
… Diego Marcheggiani and Laura Perez-Beltrachini. 2018. Deep Graph Convolutional Encoders for Structured Data to Text Generation. In Proceed- ings of the 11th International Conference on Nat- ural Language Generation, pages 1–9, Tilburg Uni- versity, The Netherlands …

Constrained decoding for neural NLG from compositional representations in task-oriented dialogue
A Balakrishnan, J Rao, K Upasani, M White… – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue Anusha Balakrishnan? Jinfeng Rao* Kartikeya Upasani* Michael White*† and Rajen Subba* Facebook Conversational AI …

CS/IT Honours Final Paper 2019
M Poulter – projects.cs.uct.ac.za
… comparing their naturalness. KEYWORDS Natural Language Generation, Data-to-text Generation, Template- based Natural Language Generation, Data-driven Natural Language Generation, Text Analysis 1 INTRODUCTION …

Revisiting the Binary Linearization Technique for Surface Realization
Y Puzikov, C Gardent, I Dagan, I Gurevych – Proceedings of The 12th …, 2019 – aclweb.org
Page 1. Proceedings of The 12th International Conference on Natural Language Generation, pages 268–278, Tokyo, Japan, 28 Oct – 1 Nov, 2019. c 2019 Association for Computational Linguistics 268 Revisiting the Binary Linearization Technique for Surface Realization …

Surface Realization Shared Task 2019 (MSR19): The Team 6 Approach
TC Ferreira, E Krahmer – Proceedings of the 2nd Workshop on …, 2019 – aclweb.org
… Association for Computa- tional Linguistics. Thiago Castro Ferreira, Chris van der Lee, Emiel van Miltenburg, and Emiel Krahmer. 2019. Neu- ral data-to-text generation: A comparison be- tween pipeline and end-to-end architectures. arXiv preprint arXiv:1908.09022 …

Neural relation extraction for knowledge base enrichment
B Distiawan, G Weikum, J Qi, R Zhang – … of the 57th Annual Meeting of …, 2019 – aclweb.org
Page 1. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 229–240 Florence, Italy, July 28 – August 2, 2019. c 2019 Association for Computational Linguistics 229 Neural Relation Extraction for Knowledge Base Enrichment …

Surface realisation using full delexicalisation
A Shimorina, C Gardent – 2019 – hal.archives-ouvertes.fr
… across languages. 1 Introduction Surface realisation maps a meaning representation to a sentence. In data-to-text generation, it is part of a complex process aiming to select, compress and structure the input data into a text. In text …

Curate and generate: A corpus and method for joint control of semantics and style in neural nlg
S Oraby, V Harrison, A Ebrahimi, M Walker – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. Curate and Generate: A Corpus and Method for Joint Control of Semantics and Style in Neural NLG Shereen Oraby, Vrindavan Harrison, Abteen Ebrahimi, and Marilyn Walker Natural Language and Dialog Systems …

Neural Relation Extraction for Knowledge Base Enrichment.
BD Trisedya, G Weikum, J Qi, R Zhang – ACL (1), 2019 – people.eng.unimelb.edu.au
Page 1. Neural Relation Extraction for Knowledge Base Enrichment Bayu Distiawan Trisedya1, Gerhard Weikum2, Jianzhong Qi1, Rui Zhang1? 1 The University of Melbourne, Australia 2 Max Planck Institute for Informatics, Saarland …

Reinforcement adaptation of an attention-based neural natural language generator for spoken dialogue systems
M Riou, B Jabaian, S Huet, F Lefèvre – Dialogue & Discourse, 2019 – 129.70.43.92
Page 1. Dialogue & Discourse 10(1) (2019) 1–19 doi: 10.5087/dad.2019.101 Reinforcement adaptation of an attention-based neural natural language generator for spoken dialogue systems Matthieu Riou MATTHIEU.RIOU@ALUMNI.UNIV-AVIGNON.FR …

Proceedings of the 22nd Nordic Conference on Computational Linguistics
M Hartmann, B Plank – Proceedings of the 22nd Nordic Conference on …, 2019 – aclweb.org
… 222 Bjarte Johansen Projecting named entity recognizers without annotated or parallel corpora . . . . . 232 Jue Hou, Maximilian Koppatz, José María Hoya Quecedo and Roman Yangarber Template-free Data-to-Text Generation of Finnish Sports News …

Algorithms and bots applied to journalism. The case of Narrativa Inteligencia Artificial: structure, production and informative quality.
MJ Ufarte Ruiz, JL Manfredi Sánchez – Doxa Comunicación, 2019 – researchgate.net
… In addition, there is Antonio Moratilla, a computer scientist and expert in big data/software who collaborates with Narrativa Inteligencia Artificial through the Research Chair “Artificial Intelligence and Data to Text Generation”, which focuses on research and development of big …

SemBleu: A robust metric for AMR parsing evaluation
L Song, D Gildea – arXiv preprint arXiv:1905.10726, 2019 – arxiv.org
… AMR graphs. SEMBLEU extends BLEU (Papineni et al., 2002), which has been shown to be effec- tive for evaluating a wide range of text generation tasks, such as machine translation and data-to-text generation. In general …

Understanding and Generating Multi-Sentence Texts
RK Kedziorski – 2019 – digital.lib.washington.edu
Page 1. Understanding and Generating Multi-Sentence Texts Rik Koncel-Kedziorski A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2019 Reading Committee: Hannaneh Hajishirzi, Chair …

Houses Bombing in Ravixe: a Bench for High Level Fusion Evaluation
N Museux, C Laudy, MC Florea – 2019 22th International …, 2019 – ieeexplore.ieee.org
… Existing systems for data-to-text generation are already used in different domains such as weather reports [10], financial reports [11], news reports [12] or sports reports [13]. The NLG process can be as simple as generating a list of pre-defined canned text …

NEAL Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa), September 30-October 2, Turku, Finland
M Hartman, B Plank – 2019 – ep.liu.se
… 167:025 Jenna Kanerva, Samuel Rönnqvist, Riina Kekki, Tapio Salakoski, Filip Ginter Template-free Data-to-Text Generation of Finnish Sports News [Abstract and Fulltext]. 167:026 Eva Pettersson, Beáta Megyesi Matching Keys and Encrypted Manuscripts [Abstract and Fulltext] …

Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction
T Nayak, HT Ng – arXiv preprint arXiv:1911.09886, 2019 – arxiv.org
Page 1. Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction Tapas Nayak and Hwee Tou Ng Department of Computer Science National University of Singapore nayakt@u.nus.edu, nght@comp.nus.edu.sg Abstract …

Graph Neural Net-Based User Simulator
X Nie, Z Lin, X Huang, Y Zhang – China National Conference on Chinese …, 2019 – Springer
… In: Proceedings of the International Conference on Learning Representations, ICLR (2016)Google Scholar. 18. Marcheggiani, D., Perez-Beltranchini, L.: Deep graph convolutional encoders for structured data to text generation …

Generating justifications for norm-related agent decisions
D Kasenberg, A Roque, R Thielstrom… – arXiv preprint arXiv …, 2019 – arxiv.org
Page 1. arXiv:1911.00226v1 [cs.CL] 1 Nov 2019 Generating Justifications for Norm-related Agent Decisions Daniel Kasenberg*, Antonio Roque, Ravenna Thielstrom, Meia Chita-Tegmark, and Matthias Scheutz Human-Robot …

IDEL: In-database neural entity linking
T Kilias, A Löser, F Gers, Y Zhang… – … Conference on Big …, 2019 – ieeexplore.ieee.org
Page 1. IDEL: In-Database Neural Entity Linking Torsten Kilias, Alexander Löser, Felix Gers Beuth University of Applied Sciences Luxemburger Straße 10 13353 Berlin, Germany {tkilias,aloeser,gers}@beuth-hochschule.de Ying …

Neural Language Priors
J Enguehard, D Busbridge, V Zhelezniak… – arXiv preprint arXiv …, 2019 – arxiv.org
… Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks. Diego Marcheggiani and Laura Perez-Beltrachini. 2018. Deep Graph Convolutional Encoders for Structured Data to Text Generation. pages 1–9. Diego Marcheggiani and Ivan Titov. 2017 …

Open Relation Extraction for Chinese Noun Phrases
C Wang, X He, A Zhou – IEEE Transactions on Knowledge and …, 2019 – ieeexplore.ieee.org
Page 1. 1041-4347 (c) 2019 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume …
J Burstein, C Doran, T Solorio – Proceedings of the 2019 Conference of …, 2019 – aclweb.org
Page 1. NAACL HLT 2019 The 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Proceedings of the Conference Vol. 1 (Long and Short Papers) June 2 – June 7, 2019 Page 2 …

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
A Korhonen, D Traum, L Màrquez – … of the 57th Annual Meeting of the …, 2019 – aclweb.org
Page 1. ACL 2019 The 57th Annual Meeting of the Association for Computational Linguistics Proceedings of the Conference July 28 – August 2, 2019 Florence, Italy Page 2. Diamond Sponsors: Platinum Sponsors: ii Page 3. Gold sponsors: Keiosk Analytics Silver sponsors …

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language …
K Inui, J Jiang, V Ng, X Wan – Proceedings of the 2019 Conference on …, 2019 – aclweb.org
Page 1. EMNLP-IJCNLP 2019 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing Proceedings of the Conference November 3–7, 2019 Hong Kong, China Page 2 …