[PDF] Top 20 Sequence based Structured Prediction for Semantic Parsing
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Sequence based Structured Prediction for Semantic Parsing
... for semantic parsing that uses a recurrent neural net- work to map a natural language question into a logical form representation of a KB ...are structured objects obeying certain constraints, are ... See full document
10
Context Dependent Semantic Parsing over Temporally Structured Data
... The number of annotated real interactions is too small for training an effective semantic parsing model. To increase the number of training exam- ples, we designed and implemented an artificial data ... See full document
10
Neural Semantic Parsing with Type Constraints for Semi Structured Tables
... Semantic parsing is the problem of translating hu- man language into computer language, and there- fore is at the heart of natural language understand- ...typical semantic parsing task is ... See full document
11
End-to-End Discourse Parsing with Cascaded Structured Prediction
... In this context of previous discussion, we refer to the work: “Surface-based Cohesive relations” by Halliday & Hasan (1976)[9]. This is the one earliest works that aims to describe how English texts are ... See full document
141
Structured prediction models for RNN based sequence labeling in clinical text
... Clinical Event categories in this corpus are Ad- verse Drug Event (ADE), Drugname , Indication and Other Sign Symptom and Diseases (Other SSD). ADE, Indication and Other SSD are events having a common vocabulary of Sign, ... See full document
10
Classical Structured Prediction Losses for Sequence to Sequence Learning
... All sequence-level models are initialized with pa- rameters of a token-level model before anneal- ...train sequence-level models for an- other 10 to 20 epochs depending on the ...configuration based ... See full document
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Bandit Structured Prediction for Neural Sequence to Sequence Learning
... Bandit structured prediction describes a stochastic optimization framework where learning is performed from partial feed- ...neural sequence-to-sequence learning problems using ... See full document
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Structured Prediction with Output Embeddings for Semantic Image Annotation
... 2,000 semantic tuples of predicate, ac- tor and ...predict semantic tuples from captions using standard shal- low and deep linguistic features ...pendency parsing, semantic role ... See full document
6
Semantic Dependency Parsing using N best Semantic Role Sequences and Roleset Information
... As mentioned by Pradhan et al. (2004), ar- gument identification poses a significant bottle- neck to improving performance of Semantic Role Labeling system. We tried an algorithm moti- vated from Hacioglu (2004) ... See full document
5
Punctuation Prediction with Transition based Parsing
... Standard automatic speech recognizers output un- structured streams of words. They neither perform a proper segmentation of the output into sentences, nor predict punctuation symbols. The unavailable punctuations ... See full document
9
Structured Training for Neural Network Transition Based Parsing
... Transition-based parsers (Nivre, 2008) have been shown to provide a good balance between efficiency and accuracy. In transition-based pars- ing, sentences are processed in a linear left to right pass; at ... See full document
11
Semantic Kernels for Semantic Parsing
... for sequence labeling such as Conditional Random Fields (CRFs) (Lafferty et ...discourse parsing with slightly better results (Saleh et ...for semantic pars- ing, i.e., rerankers based on ... See full document
7
Multilingual Semantic Parsing : Parsing Multiple Languages into Semantic Representations
... a semantic parsing model under an existing ...making semantic parsing predictions, leading to an improved multilingual semantic parsing ...bilingual parsing has been ... See full document
11
StructVAE: Tree structured Latent Variable Models for Semi supervised Semantic Parsing
... trainable semantic parser, with the correspond- ing MRs forming the structured latent semantic ...parser based on the Abstract Syntax Descrip- tion Language (ASDL) framework (Wang et ...other ... See full document
12
Multi Task Semantic Dependency Parsing with Policy Gradient for Learning Easy First Strategies
... DM parsing of the sentence “The man went back and spoke to the desk ...final parsing state, depending on the orders of creating the ...IPS parsing, some arcs are easy to pre- dict; others are very ... See full document
11
Accurate SHRG Based Semantic Parsing
... a sequence-to-sequence model and leverage the power of deep learning technolo- gies to obtain auxiliary symbols to transform the output sequence into a graph (Peng et ...casts parsing as the ... See full document
11
Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback
... Bandit structured prediction is the task of learning to solve complex joint prediction problems (like parsing or machine translation) under a very lim- ited feedback model: a system must ... See full document
11
Distilling Knowledge for Search based Structured Prediction
... In Section 4.2, improvements from distilling the ensemble have been witnessed in both the transition-based dependency parsing and neural machine translation experiments. However, ques- tions like “Why the ... See full document
10
Compositional Semantic Parsing on Semi Structured Tables
... HTML tables as follows. We randomly selected data tables from Wikipedia with at least 8 rows and 5 columns. We then created two Amazon Mechan- ical Turk tasks. The first task asks workers to write trivia questions about ... See full document
11
Grammatical Sequence Prediction for Real Time Neural Semantic Parsing
... While sequence-to-sequence (seq2seq) mod- els achieve state-of-the-art performance in many natural language processing tasks, they can be too slow for real-time ...for semantic parsing, where ... See full document
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