[PDF] Top 20 Compositional pre training for neural semantic parsing
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Compositional pre training for neural semantic parsing
... for training. Training the model in mini-batches resulted in significant speedups and allowed us to conduct many more ...the training data with an equal number of augmented examples in the cases that ... See full document
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A Re ranking Model for Dependency Parser with Recursive Convolutional Neural Network
... convolutional neural net- work (RCNN) architecture to capture the syntac- tic and compositional-semantic representations of phrases and ...k-ary parsing tree, there- fore RCNN is very suitable ... See full document
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Weakly Supervised Neural Semantic Parsing with a Generative Ranker
... Weakly-supervised semantic parsers are trained on utterance-denotation pairs, treating logical forms as ...a neural parser-ranker system for weakly-supervised semantic ...scheduled training ... See full document
12
Neural Semantic Parsing over Multiple Knowledge bases
... by training character- level models that learn to map language phrases to KB constants across datasets, and by pre-training language side models that improve the encoder from data that is independent ... See full document
6
Neural Shift Reduce CCG Semantic Parsing
... perform beam search to recover the top-k parses. The beam contains configurations. At each step, we expand all configurations with all actions, and keep only the top-k new configurations. To promote di- versity in the ... See full document
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Robust Incremental Neural Semantic Graph Parsing
... MRS makes an explicit distinction between sur- face and abstract predicates (by convention surface predicates are prefixed by an underscore). Surface predicates consist of a lemma followed by a coarse part-of-speech tag ... See full document
12
Coarse to Fine Decoding for Neural Semantic Parsing
... In this paper we presented a coarse-to-fine de- coding framework for neural semantic parsing. We first generate meaning sketches which abstract away from low-level information such as argu- ments and ... See full document
12
Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models
... space semantic parsing (VSSP), a general framework for building compositional models of vector space ...and semantic types rep- resenting vectors and functions on ...CCG semantic ... See full document
10
Linguistic Information in Neural Semantic Parsing with Multiple Encoders
... data, training is stopped after 15 ...stop training after 6 epochs, after which we restart the training process from that checkpoint to finetune on only the gold data, also for 6 ... See full document
8
Semantic graph parsing with recurrent neural network DAG grammars
... less training data; during grammar extraction we could not process around 20K sentences and in some cases could not recon- struct the whole graph, as shown by the conversion ... See full document
10
Structured Training for Neural Network Transition Based Parsing
... We conduct our experiments on two English lan- guage benchmarks: (1) the standard Wall Street Journal (WSJ) part of the Penn Treebank (Marcus et al., 1993) and (2) a more comprehensive union of publicly available ... See full document
11
Neural Semantic Parsing with Type Constraints for Semi Structured Tables
... The training set comes divided into 5 cross-validation folds for development using an 80/20 ...one training fold, using the respective development set to perform early ... See full document
11
Semantic Parsing of Pre university Math Problems
... additional training is very large at small N s and still significant at N = ...CCG parsing only with the shallow dependency annotation on in-domain ... See full document
11
Grammatical Sequence Prediction for Real Time Neural Semantic Parsing
... with neural models in a number of recent papers on seman- tic parsing (Yin and Neubig, 2017, 2018; Krish- namurthy et ...the training of the neural network model and to restrict the de- ... See full document
10
AdaNSP: Uncertainty driven Adaptive Decoding in Neural Semantic Parsing
... Neural semantic parsers utilize the encoder- decoder framework to learn an end-to-end model for semantic parsing that transduces a natural language sentence to the formal se- mantic ...can ... See full document
6
Parsing with Compositional Vector Grammars
... in parsing accuracy. Our compositional distributed representation al- lows a CVG parser to make accurate parsing de- cisions and capture similarities between phrases and ... See full document
11
Dealing with Co reference in Neural Semantic Parsing
... character-level neural semantic parsing method of van Noord and Bos ...process, pre-processing and post-processing steps are ...in neural semantic parsing and to show the ... See full document
9
Neural Architectures for Multilingual Semantic Parsing
... tic parsing – the task of mapping natural lan- guage sentences coming from multiple different languages into their corresponding formal seman- tic ...Unfortunately, training a model for each language ... See full document
7
Reranking for Neural Semantic Parsing
... Semantic parsing considers the task of trans- ducing natural language (NL) utterances into machine executable meaning representations ...While neural network-based seman- tic parsers have achieved ... See full document
7
Compositional Semantic Parsing across Graphbanks
... Non-decomposable graphs. While some en- codings of graphs as trees are lossy (Agi´c et al., 2015), ours is not: when we obtain an AM depen- dency tree from a graph, that dependency tree eval- uates uniquely to the ... See full document
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