Surface Realisation Using Full Delexicalisation

Surface realisation (SR) maps a meaning representation to a sentence and can be viewed as consisting of three subtasks: word ordering, morphological inflection and contraction generation (e.g., clitic attachment in Portuguese or elision in French). We propose a modular approach to surface realisation which models each of these components separately, and evaluate our approach on the 10 languages covered by the SR'18 Surface Realisation Shared Task shallow track. We provide a detailed evaluation of how word order, morphological realisa-tion and contractions are handled by the model and an analysis of the differences in word ordering performance across languages.

[1]  Rico Sennrich,et al.  Neural Machine Translation of Rare Words with Subword Units , 2015, ACL.

[2]  Anil Kumar Singh,et al.  IIT (BHU) Varanasi at MSR-SRST 2018: A Language Model Based Approach for Natural Language Generation , 2019, ArXiv.

[3]  Emiel Krahmer,et al.  Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach , 2018 .

[4]  Yue Zhang,et al.  Joint Morphological Generation and Syntactic Linearization , 2014, AAAI.

[5]  Thiago Alexandre Salgueiro Pardo,et al.  NILC-SWORNEMO at the Surface Realization Shared Task: Exploring Syntax-Based Word Ordering using Neural Models , 2018 .

[6]  Ondrej Dusek,et al.  Training a Natural Language Generator From Unaligned Data , 2015, ACL.

[7]  Iryna Gurevych,et al.  BinLin: A Simple Method of Dependency Tree Linearization , 2018 .

[8]  Anja Belz,et al.  The First Surface Realisation Shared Task: Overview and Evaluation Results , 2011, ENLG.

[9]  Andreas Vlachos,et al.  Sheffield at E2E: structured prediction approaches to end-to-end language generation. , 2018 .

[10]  Naoaki Okazaki,et al.  Neural Headline Generation on Abstract Meaning Representation , 2016, EMNLP.

[11]  Philip Gage,et al.  A new algorithm for data compression , 1994 .

[12]  Alessandro Mazzei,et al.  The DipInfo-UniTo system for SRST 2018 , 2018 .

[13]  Salim Roukos,et al.  Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.

[14]  Robert Weißgraeber,et al.  AX Semantics’ Submission to the Surface Realization Shared Task 2018 , 2018 .

[15]  R. H. Baayen,et al.  The CELEX Lexical Database (CD-ROM) , 1996 .

[16]  Eric P. Xing,et al.  Concise Integer Linear Programming Formulations for Dependency Parsing , 2009, ACL.

[17]  Markus Dreyer,et al.  Latent-Variable Modeling of String Transductions with Finite-State Methods , 2008, EMNLP.

[18]  Ryan Cotterell,et al.  The SIGMORPHON 2016 Shared Task—Morphological Reinflection , 2016, SIGMORPHON.

[19]  Christopher D. Manning,et al.  Get To The Point: Summarization with Pointer-Generator Networks , 2017, ACL.

[20]  Katrin Kirchhoff,et al.  Factored Neural Language Models , 2006, NAACL.

[21]  Leo Wanner,et al.  Broad Coverage Multilingual Deep Sentence Generation with a Stochastic Multi-Level Realizer , 2010, COLING.

[22]  Yoav Goldberg,et al.  Morphological Inflection Generation with Hard Monotonic Attention , 2016, ACL.

[23]  John DeNero,et al.  Supervised Learning of Complete Morphological Paradigms , 2013, NAACL.

[24]  Leo Wanner,et al.  The First Multilingual Surface Realisation Shared Task (SR’18): Overview and Evaluation Results , 2018 .

[25]  David Vandyke,et al.  Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems , 2015, EMNLP.

[26]  Fei Liu,et al.  Abstract Meaning Representation for Multi-Document Summarization , 2018, COLING.

[27]  Yue Zhang,et al.  Transition-Based Deep Input Linearization , 2017, EACL.

[28]  Tomas Mikolov,et al.  Enriching Word Vectors with Subword Information , 2016, TACL.

[29]  Henry Elder,et al.  Generating High-Quality Surface Realizations Using Data Augmentation and Factored Sequence Models , 2018, ArXiv.

[30]  Diego Marcheggiani,et al.  Deep Graph Convolutional Encoders for Structured Data to Text Generation , 2018, INLG.

[31]  David L. King,et al.  The OSU Realizer for SRST ‘18: Neural Sequence-to-Sequence Inflection and Incremental Locality-Based Linearization , 2018 .

[32]  Christopher D. Manning,et al.  Effective Approaches to Attention-based Neural Machine Translation , 2015, EMNLP.