Notes:
Combinatory categorial grammar (CCG) parsers are software systems that are used to analyze and understand the structure and meaning of natural language sentences. They are based on the theory of combinatory categorial grammar, which is a formal system for describing the syntactic and semantic structure of natural language sentences.
CCG parsers work by analyzing the syntactic structure of a sentence and assigning a meaning to each word or phrase in the sentence based on its syntactic category. The syntactic categories are determined by the way the words are combined to form phrases and sentences, and the meanings of the words and phrases are represented using logical formulas.
CCG parsers are used in a variety of applications, such as natural language processing, information extraction, machine translation, and language generation. They can be used to understand the meaning of a sentence, to identify the main concepts and relationships in a text, or to generate a translation of a sentence in another language.
CCG parsers are typically implemented using computational techniques, such as machine learning or rule-based systems, and they can be integrated into a variety of applications or platforms. They are a useful tool for understanding and analyzing the structure and meaning of natural language sentences, and they can be used to facilitate a wide range of natural language processing tasks.
- Data-driven parsing refers to a type of natural language processing technique that involves using large datasets of annotated text to train a parser to recognize the syntactic and semantic structure of sentences. Data-driven parsing relies on machine learning algorithms to analyze the patterns and relationships in the data and learn how to parse sentences based on those patterns.
- Generative CCG parsing refers to a type of parsing technique that is based on the theory of combinatory categorial grammar (CCG). Generative CCG parsing involves using a set of rules and principles to generate all possible parses for a given sentence, and then selecting the parse that is most likely to be correct based on the context and the meaning of the words and phrases in the sentence.
- Treebanking refers to the process of annotating a text with information about its syntactic and semantic structure, typically by creating a tree-like representation of the sentence or phrase structure. Treebanking is often used to create datasets that can be used to train natural language processing systems, such as parsers or machine translation systems.
- Unsupervised tagging refers to a type of natural language processing technique that involves using machine learning algorithms to automatically tag words or phrases in a text with their syntactic or semantic categories, without the use of pre-labeled training data. Unsupervised tagging relies on the patterns and relationships in the data to learn how to classify the words and phrases in the text.
Resources:
- ccgbank .. translation of the penn treebank into a corpus of ccg derivations
- software .. incomplete list of links to ccg software
Wikipedia:
References:
See also:
Combinatory Categorial Grammar & Natural Language Generation | OpenCCG (OpenNLP CCG Library)
Max-Margin Incremental CCG Parsing
M Stanojevi?, M Steedman – Proceedings of the 58th Annual Meeting of …, 2020 – aclweb.org
Incremental syntactic parsing has been an active research area both for cognitive scientists trying to model human sentence processing and for NLP researchers attempting to combine incremental parsing with language modelling for ASR and MT. Most effort has been directed …
Translate Japanese into Formal Languages with an Enhanced Generalization Algorithm
K Kashihara – Science and Information Conference, 2020 – Springer
… Japanese sentence. Thus, we introduce Phrase Override that trims the output CCG parse tree, by the Japanese CCG parser. This Phrase Override algorithm is applicable to the other languages’ CCG parsers. 3.1 Phrase Override …
Supertagging Combinatory Categorial Grammar with Attentive Graph Convolutional Networks
Y Tian, Y Song, F Xia – arXiv preprint arXiv:2010.06115, 2020 – arxiv.org
… Abstract Supertagging is conventionally regarded as an important task for combinatory categorial grammar (CCG) parsing, where effective mod- eling of contextual information is highly im- portant to this task … 2016. LSTM CCG Parsing …
Studies on Efficient Parsing and Logic-based Inference based on Combinatory Categorial Grammar
???? – 2020 – isw3.naist.jp
… The first contribution of this presentation is the development of an accurate and efficient CCG parser … Second, we work on the domain adaptation issue of CCG parsing, since we are interested in applications of CCG-based inference systems in various domains such as scientific …
Logical inferences with comparatives and generalized quantifiers
I Haruta, K Mineshima, D Bekki – arXiv preprint arXiv:2005.07954, 2020 – arxiv.org
… 3 Experiments 3.1 Experimental settings For CCG parsing, we use two CCG parsers, namely, C&C (Clark and Curran, 2007) and de- pccg (Yoshikawa et al., 2017), to mitigate parsing errors. If two parsers output a different answer, we …
Combining Event Semantics and Degree Semantics for Natural Language Inference
I Haruta, K Mineshima, D Bekki – arXiv preprint arXiv:2011.00961, 2020 – arxiv.org
… 3 Experiments Experimental settings We use three CCG parsers, namely, C&C (Clark and Curran, 2007), Easy- CCG (Lewis and Steedman, 2014), and depccg (Yoshikawa et al., 2017), for CCG parsing, and we use Tsurgeon (Levy and Andrew, 2006) for tree transformation …
Generating CCG Categories
Y Liu, T Ji, Y Wu, M Lan – arXiv preprint arXiv:2103.08139, 2021 – arxiv.org
… Main Results Table 2 lists overall performances on CCGBank. C&C is a non-neural-network-based CCG parser, (Lewis, Lee, and Zettlemoyer 2016) is a LSTM-based supertagger similar to our CC model (with less parameters) …
Why Names and Numbers Need Semantics
G Marton, MW Bilotti, S Tellex – people.csail.mit.edu
… We demonstrate a proof-of- concept CCG parser and lexicon for nu- meric expressions and names, and eval- uate it on the MUC-7 named-entity task. 1 Introduction … Page 2. We envision a CCG parser that can fully exam- ine the internal semantics of its named entities …
Towards a DRS Parsing Framework for French
Y Haralambous, P Lenca – core.ac.uk
… For English, one can obtain CCG derivations by using a CCG parser such as C&C Parser [10], EasyCCG [11], or OpenCCG1 … B. Combinatory Categorial Grammar Parsing … We then obtain a CCG derivation tree as output of the CCG parsing stage. The results are represented (cf …
Development of a General-Purpose Categorial Grammar Treebank
Y Kubota, K Mineshima, N Hayashi… – Proceedings of The 12th …, 2020 – aclweb.org
… Mineshima, K., Tanaka, R., Mart?nez-Gómez, P., Miyao, Y., and Bekki, D. (2016). Building compositional se- mantics and higher-order inference system for a wide- coverage Japanese CCG parser … A* CCG parsing with a supertag and dependency factored model …
Katanov State University of Khakasia
VA Yatsko – researchgate.net
… Chapter seven entitled “Investigating the effect of automatic MWE recognition on CCG parsing” is written by Myriam de Lhoneux, Omri Abend, and Mark Steedman … To test how MWE recognition affects CCG parsing the authors suggest first recognizing …
The Parallel Meaning Bank: A Framework for Semantically Annotating Multiple Languages
L Abzianidze, R van Noord, C Wang, J Bos – arXiv preprint arXiv …, 2020 – arxiv.org
… As syntactic analyses play a key role for obtaining meaning representations in the PMB because they contribute to defining lexical semantics and guiding compo- sition of phrasal semantics, a quick integration required a Japanese CCG parser in the PMB pipeline …
HybridCite: A Hybrid Model for Context-Aware Citation Recommendation
M Färber, A Sampath – Proceedings of the ACM/IEEE Joint Conference …, 2020 – dl.acm.org
Page 1. HybridCite: A Hybrid Model for Context-Aware Citation Recommendation Michael Färber Karlsruhe Institute of Technology (KIT) Karlsruhe, Germany michael.faerber@kit.edu Ashwath Sampath University of Freiburg Freiburg, Germany ashwath92@gmail.com …
Learning as Abduction: Trainable Natural Logic Theorem Prover for Natural Language Inference
L Abzianidze – arXiv preprint arXiv:2010.15909, 2020 – arxiv.org
… Another adopted criterion for the best T-sets is 5For each term, a head and a syntactic category can be de- tected using POS tags and CCG categories, which are assigned by a CCG parser and kept in the term representation …
Supertagging with CCG primitives
A Bhargava, G Penn – Proceedings of the 5th Workshop on …, 2020 – aclweb.org
… But since an incor- rect lexical category can impair the parsability of a full sentence, it is more appropriate to consider the number of affected sentences, which is 0.9% for both the development and test sets.3 Work on CCG parsers has noted their high sensitivity to su- pertagging …
SOLVING TEXTUAL ENTAILMENT WITH THE THEOREM PROVER FOR NATURAL LANGUAGE
L Abzianidze – viam.science.tsu.ge
… In the running 8The ccg terms are typed with the syntactic types corresponding to the ccg cate- gories. They are not well-formed ?-terms due to the remains of the type changing (ie lexical) combinatory rule of the ccg parsers … There are no men sawing CCG parser CCG parser …
Hierarchical Query Graph Generation for Complex Question Answering over Knowledge Graph
Y Qiu, K Zhang, Y Wang, X Jin, L Bai, S Guan… – Proceedings of the 29th …, 2020 – dl.acm.org
… Page 2. graphs to represent the semantic structures of questions, as shown in Figure 1. In [18, 19, 33], questions are first converted to semantic graphs via a parser, eg, Combinatory Categorial Grammar (CCG) parser and dependency parser …
CCG Supertagging as Top-down Tree Generation
J Prange, N Schneider… – Proceedings of the …, 2021 – scholarworks.umass.edu
… as seman- tic parsing and machine translation. Most CCG parsers operate as a pipeline whose first task is ‘su- pertagging’, ie, sequence labeling with a large search space of complex tags. Given these su- pertags, all that remains …
A Semantic Calculus: Common Sense Reasoning for Information Systems
R Lewis – Proceedings of the 2019 11th International Conference …, 2020 – dl.acm.org
… Connecting the aforementioned modal ?-calculus, ?ML, modal logic to CCG’s ?-calculus component as illustrated in Figure 2 we turn to a variant Lewis et al.’s supertagging based on their stacked bi-directional long short term memory (LSTM) CCG parsing model [28] where we …
Supertagging the Long Tail with Tree-Structured Decoding of Complex Categories
J Prange, N Schneider, V Srikumar – arXiv preprint arXiv:2012.01285, 2020 – arxiv.org
… 2017). Most CCG parsers operate as a pipeline whose first task is ‘supertagging’, ie, sequence labeling with a large search space of complex ‘supertags’ (Clark and Curran, 2004; Xu et al., 2015; Vaswani et al., 2016, inter alia) …
Configurable Dependency Tree Extraction from CCG Derivations
K Evang – Proceedings of the Fourth Workshop on Universal …, 2020 – treegrasp.phil.hhu.de
… Clark, S., Hockenmaier, J., and Steedman, M. (2002). Building deep dependency structures using a wide-coverage CCG parser. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pages 327–334, Philadelphia, Pennsylvania, USA …
Putting Humans in the Natural Language Processing Loop: A Survey
ZJ Wang, D Choi, S Xu, D Yang – arXiv preprint arXiv:2103.04044, 2021 – arxiv.org
… Parsing in NLP is a process to determine the syntactic structure of the input text. Entity linking aims to assign unique identity to entities in the text, such as names and locations. Advancing traditional Combinatory Categorial Grammars (CCG) parsers, He et al …
Teaching machine comprehension with compositional explanations
Q Ye, X Huang, X Ren – arXiv preprint arXiv:2005.00806, 2020 – arxiv.org
… One collected explanation will first go through a Combi- natory Categorial Grammar (CCG) parser (Zettlemoyer & Collins, 2012) and is … These predicate implementations, together with the inherent ?-calculus hierarchy from CCG parsing, will yield the final executable function fj …
Combinatory Categorial Grammar for Hebrew
E Agami – 2020 – idc.ac.il
… 20 2.6 CCG Parsing and Probability Modeling … We aim to create a Hebrew CCG treebank, and a statistical CCG parser trained on it … Modern CCG parsers use super- taggers based on Recurrent Nerual Networks (RNNs) for both accuracy and fast parsing times …
Linguistic Semantics and Contemporary NLI
M Steedman – 2020 – typo.uni-konstanz.de
… We have trained an entailment graph on the NewsSpike corpus – 0.5M multiply-sourced news articles over 2 months, 20M sentences. – 29M binary relation tokens extracted using the CCG parser. • We have built a working typed global entailment graph, collapsing paraphrase …
Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing
B Hui, R Geng, Q Ren, B Li, Y Li, J Sun… – arXiv preprint arXiv …, 2021 – arxiv.org
… denotation (Berant and Liang 2014) in- stead. Zettlemoyer and Collins (2009) propose a context- independent CCG parser and then applied it to do context- dependent substitution. Furthermore, Suhr, Iyer, and Artzi (2018) generate …
Knowledge Bases And Statistical Natural Language Processing
R Bandpey – researchgate.net
… Their model consist of a rule-based semantic parser and a probabilistic database. Their semantic parser uses a syntactic CCG parser and manually-defined rules to map entity-linked texts to logical forms in which every predicates derived from the words in the text …
Supertagging the Long Tail with Tree-Structured Decoding of Complex Categories
JPN Schneider, V Srikumar – prange.jakob.georgetown.domains
… 2017). Most CCG parsers operate as a pipeline whose first task is ‘supertagging’, ie, sequence labeling with a large search space of complex ‘supertags’ (Clark and Curran, 2004; Xu et al., 2015; Vaswani et al., 2016, inter alia) …
An agent for learning new natural language commands
A Azaria, S Srivastava, J Krishnamurthy… – Autonomous Agents and …, 2020 – Springer
… Thomason et al. [58] use CCG parsing on natural language commands in order for a robot to execute them. They use conversations with previous users to better understand user commands as well as overcome typos and spelling mistakes. Quirk et al …
VASTA: a vision and language-assisted smartphone task automation system
AR Sereshkeh, G Leung, K Perumal, C Phillips… – Proceedings of the 25th …, 2020 – dl.acm.org
… SUGILITE’s [17] conversational agent employs a Learn- ing by Instruction Agent (LIA) [1] that parses verbal commands with a Combinatory Categorical Grammar (CCG) parser [31], which requires hand-engineering of lexicalized rules …
Semantic Parsing for Text Analytics-IDA
M Kuhlmann – 2020 – ida.liu.se
… [P11] Marco Kuhlmann, Giorgio Satta, and Peter Jonsson. On the Complexity of CCG Parsing. Computational Linguistics, 44(3):447–482, 2018 … [P09] Marco Kuhlmann, Giorgio Satta, and Peter Jonsson. On the Complexity of CCG Parsing. CoRR, abs/1702.06594, 2017 …
A Model of Unsupervised Formal Learning for Natural Language
JN Collard – 2020 – ecommons.cornell.edu
… 114 6.1 Semantics Cell Sizes and Biases . . . . . 129 6.2 SemanticDegradation . . . . . 130 7.1 ImprovementsfromMorphology . . . . . 135 A.1 Initialized chart for CCG Parsing …
Thirty musts for meaning banking
J Bos, L Abzianidze – arXiv preprint arXiv:2005.13421, 2020 – arxiv.org
… Similarly, the meaning representations in the GMB are system-produced and partially hand-corrected (Bos et al., 2017), us- ing a CCG parser (Clark and Curran, 2004). Like- wise, the meaning representations in the PMB are …
Statistical Deep Parsing for Spanish using Neural Networks
L Chiruzzo, D Wonsever – … of the 16th International Conference on …, 2020 – aclweb.org
Page 1. Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task, pages 132–144 Virtual Meeting, July 9, 2020. c 2020 Association for Computational Linguistics 132 Statistical Deep Parsing for Spanish using Neural Networks …
A Survey on Semantic Parsing from the perspective of Compositionality
P Kumar, S Bedathur – arXiv preprint arXiv:2009.14116, 2020 – arxiv.org
… Given a sentence and its logical-expression, a rule based function GENLEX(Si,Li) creates lexicon specific to the sentence. Together with ?0, the new set ? = ?0 ? GENLEX(Si, Li) form the search space for the probabilistic CCG parser …
Semi-Automated Protocol Disambiguation and Code Generation
J Yen, T Lévai, Q Ye, X Ren, R Govindan… – arXiv preprint arXiv …, 2020 – arxiv.org
… In this example, the CCG parser generates two semantic interpretations correspond- ing to two different groupings of operations (one that groups A and B, the … Figure 3: Example of multiple LFs from CCG parsing of “For computing the checksum, the checksum should be zero” …
Montague Grammar Induction
GL Kim, AS White – Semantics and Linguistic Theory, 2021 – journals.linguisticsociety.org
Page 1. Proceedings of SALT 30: 227–251, 2020 Montague Grammar Induction* Gene Louis Kim University of Rochester Aaron Steven White University of Rochester Abstract We propose a computational modeling framework …
Robot Path Planning Algorithm Based on Particle Swarm Optimization and Feedforward Neural Network in Network Environment
SW Li – 2020 4th International Conference on Artificial …, 2020 – dl.acm.org
… fund project of Heilongjiang University (NO. KJCX201922). REFERENCES [1] Yoshikawa M, Noji H, Matsumoto Y. A* CCG Parsing with a Supertag and De- pendency Factored Model[J]. 2017. [2] Sultana S, Shehab M, Bertino …
Natural language techniques supporting decision modelers
L Arco, G Nápoles, F Vanhoenshoven, AL Lara… – Data Mining and …, 2021 – Springer
Decision Model and Notation (DMN) has become a relevant topic for organizations since it allows users to control their processes and organizational decisio.
The Role of Syntactic Planning in Compositional Image Captioning
E Bugliarello, D Elliott – arXiv preprint arXiv:2101.11911, 2021 – arxiv.org
… For IOB- based chunking, we train a classifier-based tagger on CoNLL2000 data (Tjong Kim Sang and Buch- holz, 2000) using NLTK (Bird et al., 2009). Finally, we use the A* CCG parsing model by Yoshikawa et al. (2017) with ELMo embeddings (Peters et al …
Human or Machine: Automating Human Likeliness Evaluation of NLG Texts
E Çano, O Bojar – arXiv preprint arXiv:2006.03189, 2020 – arxiv.org
… References 1. Ambati, BR, Reddy, S., Steedman, M.: Assessing relative sentence complexity using an incremental CCG parser. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics. pp. 1051–1057 …
Scientific Text Entailment and a Textual-Entailment-based framework for cooking domain question answering
A Pathak, R Manna, P Pakray, D Das, A Gelbukh… – S?dhan?, 2021 – Springer
… (b) Set-based similarities: Dice, Jaccard, Overlap and Harmonic. (c) Edit distance measures: Levenshtein distance, Smith–Waterman distance and Jaro distance. 3.1b Syntactic module: Using a Cambridge Categorical Grammar (CCG) Parser Footnote 9 [27,.
TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis
H Zhang, L Liu, H Jiang, Y Li, E Zhao, K Xu… – arXiv preprint arXiv …, 2020 – arxiv.org
… The results of semantic role labeling support many downstream tasks, such as deeper semantic analysis (AMR Parsing, CCG Parsing, etc.), intention recognition in a task-oriented dialogue system, entity scoring in knowledge-based question …
QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer
R Lorenz, A Pearson, K Meichanetzidis… – arXiv preprint arXiv …, 2021 – arxiv.org
… dinner nl n nl nr s Figure 4 tive approach would be to use a CCG parser and subsequently convert the types into pregroups. This however comes with a few caveats, the discussion of which is outside the scope of this paper. 8As discussed in Sec. 3, the diagram in Fig …
Benchmarking Meaning Representations in Neural Semantic Parsing
J Guo, Q Liu, JG Lou, Z Li, X Liu, T Xie… – Proceedings of the 2020 …, 2020 – aclweb.org
Page 1. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pages 1520–1540, November 16–20, 2020. c 2020 Association for Computational Linguistics 1520 Benchmarking Meaning Representations in Neural Semantic Parsing …
Deconstructing supertagging into multi-task sequence prediction
Z Zhu – 2020 – summit.sfu.ca
Page 1. Deconstructing Supertagging into Multi-task Sequence Prediction by Zhenqi Zhu B.Sc., Simon Fraser University, 2018 B.Eng., Zhejiang University, 2018 Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science …
Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback
A Elgohary, S Hosseini, AH Awadallah – arXiv preprint arXiv:2005.02539, 2020 – arxiv.org
… process itself. He et al. (2016) ask simplified questions about uncertain dependencies in CCG parsing and use the answers as soft con- straints to regenerate the parse. Both Li and Ja- gadish (2014) and Su et al. (2018) generate …
How far are we from effective context modeling? an exploratory study on semantic parsing in context
Q Liu, B Chen, J Guo, JG Lou, B Zhou… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. How Far are We from Effective Context Modeling ? An Exploratory Study on Semantic Parsing in Context Qian Liu1? , Bei Chen2 , Jiaqi Guo3? , Jian-Guang Lou2 , Bin Zhou1 , Dongmei Zhang2 1Beihang University …
An analysis of natural language inference benchmarks through the lens of negation
MM Hossain, V Kovatchev, P Dutta, T Kao… – Proceedings of the …, 2020 – aclweb.org
Page 1. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pages 9106–9118, November 16–20, 2020. c 2020 Association for Computational Linguistics 9106 An Analysis of Natural …
Treegen: A tree-based transformer architecture for code generation
Z Sun, Q Zhu, Y Xiong, Y Sun, L Mou… – Proceedings of the AAAI …, 2020 – ojs.aaai.org
Page 1. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) TreeGen: A Tree-Based Transformer Architecture for Code Generation Zeyu Sun, † Qihao Zhu, † Yingfei Xiong, ?† Yican Sun, † Lili Mou, ‡ Lu Zhang † …
Machine Learning for Readability Assessment and Text Simplification in Crisis Communication: A Systematic Review
H Hansen, A Widera, J Ponge… – … of the 54th …, 2021 – scholarspace.manoa.hawaii.edu
Page 1. Machine Learning for Readability Assessment and Text Simplification in Crisis Communication: A Systematic Review Hieronymus Hansen University of Münster (ERCIS) hieronymus.hansen@uni- muenster.de Adam …
Finding New Multiword Expressions for Existing Thesaurus
P Rossyaykin, N Loukachevitch – Conference on Artificial Intelligence and …, 2020 – Springer
… expression extraction. In: Proceedings of the Workshop on A Broader Perspective on Multiword Expressions, pp. 25–32 (2007)Google Scholar. 7. De Lhoneux, M.: Ccg parsing and multiword expressions. arXiv preprint arXiv …
Automating Text Naturalness Evaluation of NLG Systems
E Çano, O Bojar – arXiv preprint arXiv:2006.13268, 2020 – arxiv.org
… In: Deb, K. (ed.) Genetic and Evolutionary Computa- tion – GECCO 2004. pp. 828–839. Springer Berlin Heidelberg (2004) 2. Ambati, BR, Reddy, S., Steedman, M.: Assessing relative sentence com- plexity using an incremental CCG parser …
Learning cross-context entity representations from text
J Ling, N FitzGerald, Z Shan, LB Soares, T Févry… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. LEARNING CROSS-CONTEXT ENTITY REPRESENTA- TIONS FROM TEXT Jeffrey Ling† Nicholas FitzGerald Zifei Shan Livio Baldini Soares Thibault Févry† David Weiss Tom Kwiatkowski Google Research † Work done as a Google AI Resident …
Generating Explanations for Temporal Logic Planner Decisions
D Kasenberg, R Thielstrom, M Scheutz – Proceedings of the …, 2020 – ojs.aaai.org
Page 1. Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling (ICAPS 2020) Generating Explanations for Temporal Logic Planner Decisions Daniel Kasenberg, Ravenna Thielstrom, Matthias …
The return of lexical dependencies: Neural lexicalized pcfgs
H Zhu, Y Bisk, G Neubig – … of the Association for Computational Linguistics, 2020 – MIT Press
Create a new account. Email. Returning user. Can’t sign in? Forgot your password? Enter your email address below and we will send you the reset instructions. Email. Cancel. If the address matches an existing account you will …
SemGloVe: Semantic Co-occurrences for GloVe from BERT
L Gan, Z Teng, Y Zhang, L Zhu, F Wu… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. SemGloVe: Semantic Co-occurrences for GloVe from BERT Leilei Gan1, Zhiyang Teng2, Yue Zhang2, Linchao Zhu3, Fei Wu1, Yi Yang1 1 College of Computer Science and Technology, Zhejiang University 2 Westlake …
The first shared task on discourse representation structure parsing
L Abzianidze, R van Noord, H Haagsma… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. The First Shared Task on Discourse Representation Structure Parsing Lasha Abzianidze Rik van Noord Hessel Haagsma Johan Bos CLCG, University of Groningen {l.abzianidze, rikvan.noord, hessel.haagsma, johan.bos}@rug.nl Abstract …
Dynamic tensor rematerialization
M Kirisame, S Lyubomirsky, A Haan, J Brennan… – arXiv preprint arXiv …, 2020 – arxiv.org
… The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision, 2019. [14] Kenton Lee, Mike Lewis, and Luke Zettlemoyer. Global neural CCG parsing with optimality guarantees. CoRR, abs/1607.01432, 2016 …
French language DRS parsing
NL Le – 2020 – tel.archives-ouvertes.fr
… 93 6.5 Related CCG Parsing Works . . . . . 94 6.5.1 Chart parsing algorithms . . . . . 95 6.5.2 CCG parsing via planning . . . . . 96 6.5.3 Shift-reduce parsing algorithms …
Automatic extraction of subordinate clauses and its application in second language acquisition research
X Chen, T Alexopoulou, I Tsimpli – Behavior Research Methods, 2020 – Springer
Clause subordination is an important linguistic phenomenon that is relevant to research in psycholinguistics, cognitive and behavioral sciences, language a.
The Measurement of Chinese Sentence Semantic Complexity
S Zhu, J Song, W Peng, D Guo, J Sun – Complexity, 2020 – hindawi.com
The complexity of language is usually reflected in the complexity of sentences. At present, the research of sentence complexity mainly focuses on the analysis of syntactic complexity. In this paper, from the perspective of Leech’s theory of sentence semantic structure, the predication …
Fast semantic parsing with well-typedness guarantees
M Lindemann, J Groschwitz, A Koller – arXiv preprint arXiv:2009.07365, 2020 – arxiv.org
Page 1. Fast semantic parsing with well-typedness guarantees Matthias Lindemann and Jonas Groschwitz and Alexander Koller Department of Language Science and Technology Saarland University {mlinde|jonasg|koller}@coli.uni-saarland.de Abstract …
Mimic and Conquer: Heterogeneous Tree Structure Distillation for Syntactic NLP
H Fei, Y Ren, D Ji – arXiv preprint arXiv:2009.07411, 2020 – arxiv.org
Page 1. Mimic and Conquer: Heterogeneous Tree Structure Distillation for Syntactic NLP Hao Fei1, Yafeng Ren2 and Donghong Ji1? 1. Department of Key Laboratory of Aerospace Information Security and Trusted Computing …
Natural Language Processing: A Machine Learning Perspective
Y Zhang, Z Teng – 2021 – books.google.com
Page 1. NATURAL LANGUAGE PROCESSING AMachine Learning Perspective YUE ZHANG ZHIYANG TENG Page 2. Natural Language Processing With a machine learning approach and less focus on linguistic details, this …
Character-level Representations Still Improve Semantic Parsing in the Age of BERT
R van Noord, A Toral, J Bos – Proceedings of the 2020 Conference on …, 2020 – aclweb.org
Page 1. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pages 4587–4603, November 16–20, 2020. c 2020 Association for Computational Linguistics 4587 Character-level Representations …
Dbpal: A fully pluggable NL2SQL training pipeline
N Weir, P Utama, A Galakatos, A Crotty… – Proceedings of the …, 2020 – dl.acm.org
Page 1. DBPal: A Fully Pluggable NL2SQL Training Pipeline Nathaniel Weir1 Prasetya Utama2 Alex Galakatos3 Andrew Crotty3 Amir Ilkhechi3 Shekar Ramaswamy3 Rohin Bhushan3 Nadja Geisler2 Benjamin Hättasch2 Steffen Eger2 Ugur Cetintemel3 Carsten Binnig2 …
Understanding Natural Language Instructions for Self-Driving Cars and Grounding
N OTAWARA, A INAGO, H TSUKAHARA… – Journal of Japan …, 2020 – jstage.jst.go.jp
Page 1. 18 ????????????????????Vol.32, No.3, pp.722 – 736?2020? ???? ?????????????????????? † ??? ??????? ??????? ??????? ???? ????????????????????????????? …
Is map decoding all you need? the inadequacy of the mode in neural machine translation
B Eikema, W Aziz – arXiv preprint arXiv:2005.10283, 2020 – arxiv.org
Page 1. Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation Bryan Eikema University of Amsterdam b.eikema@uva.nl Wilker Aziz University of Amsterdam w.aziz@uva.nl Abstract Recent …
Modelling source-and target-language syntactic Information as conditional context in interactive neural machine translation
KK Gupta, R Haque, A Ekbal, P Bhattacharyya, A Way – 2020 – doras.dcu.ie
Page 1. Modelling Source- and Target-Language Syntactic Information as Conditional Context in Interactive Neural Machine Translation Kamal Kumar Gupta, Rejwanul Haque,† Asif Ekbal, Pushpak Bhattacharyya and Andy …
REVISITING RECOGNIZING TEXTUAL ENTAILMENT FOR EVALUATING NATURAL LANGUAGE PROCESSING SYSTEMS
A Poliak – 2020 – jscholarship.library.jhu.edu
Page 1. REVISITING RECOGNIZING TEXTUAL ENTAILMENT FOR EVALUATING NATURAL LANGUAGE PROCESSING SYSTEMS by Adam Poliak A dissertation submitted to The Johns Hopkins University in conformity with the …
Learning meaning representations for text generation with deep generative models
K Cao – 2020 – repository.cam.ac.uk
Page 1. Learning meaning representations for text generation with deep generative models Kris Cao Department of Computer Science University of Cambridge This dissertation is submitted for the degree of Doctor of Philosophy Clare College October 2019 Page 2. Page 3 …
Transition based Graph Decoder for Neural Machine Translation
L Choshen, O Abend – arXiv preprint arXiv:2101.12640, 2021 – arxiv.org
Page 1. Transition-based Graph Decoder for Neural Machine Translation Leshem Choshen Department of Computer Science Hebrew University of Jerusalem leshem.choshen@mail.huji.ac.il Omri Abend Department of Computer …
Report on the First Knowledge Graph Reasoning Challenge 2018
Y Hokazono, T Ugai, Y Koyanagi… – … China, November 25 …, 2020 – books.google.com
… https://en. wikipedia. org/wiki/Fauna of India. Accessed 18 Jan 2019 4. Mineshima, K., Tanaka, R., Gomez, PM, Miyao, Y., Bekki, D.: Building compo- sitional semantics and higher-order inference system for a wide-coverage Japanese CCG parser …
Semantic Role Labeling as Syntactic Dependency Parsing
T Shi, I Malioutov, O ?rsoy – arXiv preprint arXiv:2010.11170, 2020 – arxiv.org
Page 1. Semantic Role Labeling as Syntactic Dependency Parsing Tianze Shi? Cornell University tianze@cs.cornell.edu Igor Malioutov Bloomberg LP imalioutov@bloomberg. net Ozan ?Irsoy Bloomberg LP oirsoy@bloomberg.net Abstract …
Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT
R van Noord, A Toral, J Bos – arXiv preprint arXiv:2011.04308, 2020 – arxiv.org
Page 1. Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT Rik van Noord CLCG University of Groningen The Netherlands rikvannoord@gmail. com Antonio Toral CLCG University of Groningen The Netherlands a.toral.ruiz@rug.nl …
HPSG and Categorial Grammar
Y Kubota – Head-Driven Phrase Structure Grammar: The …, 2020 – hpsg.hu-berlin.de
Page 1. Chapter 30 HPSG and Categorial Grammar Yusuke Kubota National Institute for Japanese Language and Linguistics This chapter aims to offer an up-to-date comparison of HPSG and Categorial Gram- mar (CG). Since …
A Fast Filtering Algorithm for Massive Context-free Grammars
J Dohmann, K Deeds – Proceedings of the 2020 ACM Southeast …, 2020 – dl.acm.org
Page 1. A Fast Filtering Algorithm for Massive Context-free Grammars Jeremy Dohmann and Kyle Deeds Harvard College Cambridge, MA, USA {dohmann,kdeeds} @college.harvard.edu Abstract All non-statistical context-free …
Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog
A Padmakumar, R Mooney, P Stone… – Good Systems …, 2020 – repositories.lib.utexas.edu
Page 1. In The Journal of Artificial Intelligence Research (JAIR Volume 67, 2020) Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog Jesse Thomason jdtho@cs.washington.edu …
The logic of Quantifier Raising
C Barker – Semantics and Pragmatics, 2020 – semprag.org
Page 1. Semantics & Pragmatics Volume 13, Article 20, 2020 https://doi.org/10.3765/sp.13.20 This is an early access version of Barker, Chris. 2020. The logic of Quantifier Raising. Semantics and Pragmatics 13(20). https://doi.org/10.3765/sp.13.20 …
Jointly improving parsing and perception for natural language commands through human-robot dialog
J Thomason, A Padmakumar, J Sinapov… – Journal of Artificial …, 2020 – jair.org
Page 1. Journal of Artificial Intelligence Research 67 (2020) 327-374 Submitted 05/2019; published 02/2020 Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog Jesse Thomason jdtho@cs.washington.edu …
Syntax-Informed Interactive Neural Machine Translation
KK Gupta, R Haque, A Ekbal… – … Joint Conference on …, 2020 – ieeexplore.ieee.org
… [30] S. Clark and JR Curran, “The importance of supertagging for wide-coverage CCG parsing,” in COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics, Geneva, Switzerland, 2004, pp. 282–288 …
On the linguistic representational power of neural machine translation models
Y Belinkov, N Durrani, F Dalvi, H Sajjad… – Computational …, 2020 – MIT Press
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A formal universal of natural language grammar
M Steedman – Language, 2020 – muse.jhu.edu
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Data-driven sentence simplification: Survey and benchmark
F Alva-Manchego, C Scarton, L Specia – Computational Linguistics, 2020 – MIT Press
Create a new account. Email. Returning user. Can’t sign in? Forgot your password? Enter your email address below and we will send you the reset instructions. Email. Cancel. If the address matches an existing account you will …
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
D Jurafsky, J Chai, N Schluter, J Tetreault – … of the 58th Annual Meeting of …, 2020 – aclweb.org
Page 1. ACL 2020 The 58th Annual Meeting of the Association for Computational Linguistics Proceedings of the Conference July 5 – 10, 2020 Page 2. Diamond Sponsors Platinum Sponsors Gold Sponsors Silver Sponsors ii Page 3. Bronze Sponsors Supporter Sponsors …
Cross-lingual entity extraction and linking for 300 languages
X Pan – 2020 – ideals.illinois.edu
Page 1. © 2020 Xiaoman Pan Page 2. CROSS-LINGUAL ENTITY EXTRACTION AND LINKING FOR 300 LANGUAGES BY XIAOMAN PAN DISSERTATION Submitted in partial fulfillment of the requirements for the degree of …
Parsing an American Sign Language Corpus with Combinatory Categorial Grammar
MA Nix – 2020 – search.proquest.com
… BYU ScholarsArchive Theses and Dissertations 2020-03-25 Parsing an American Sign Language Corpus with Combinatory Categorial Grammar Michael Albert Nix Brigham Young University Follow this and additional works at: https://scholarsarchive.byu.edu/etd …
Neural-Symbolic Reasoning on Knowledge Graphs
J Zhang, B Chen, L Zhang, X Ke, H Ding – arXiv preprint arXiv:2010.05446, 2020 – arxiv.org
Page 1. JOURNAL OF IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. V, NO. N, JANUARY 2019 1 Neural-Symbolic Reasoning on Knowledge Graphs Jing Zhang*, Bo Chen, Lingxi Zhang, Xirui Ke, Haipeng Ding …
Deep Learning and Linguistic Representation
S Lappin – 2021 – books.google.com
Page 1. Chapman & Hall/CRC Machine Learning & Pattern Recognition Series DEEP LEARNING AND LINGUISTIC REPRESENTATION Shalom Lappin CRC CRC Press Taylor & Francis Group A CHAPMAN & HALL BOOK Page 2. Deep Learning and Linguistic Representation …