[PDF] Top 20 Syntax-Aware Neural Semantic Role Labeling
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Syntax-Aware Neural Semantic Role Labeling
... Meanwhile, inspired by the success of syntactic features in traditional SRL approaches, researchers also try to en- hance neural network based SRL approaches by syntax. He et al. (2017) show that large ... See full document
9
Chinese Semantic Role Labeling with Bidirectional Recurrent Neural Networks
... word based Chinese SRL system, which is quite different from the previous parsing based ones. Sun et al. (2009) extended the work of Chen et al. (2006), performed Chinese SRL with shallow parsing, which took partial ... See full document
6
Neural Models of Selectional Preferences for Implicit Semantic Role Labeling
... Both neural models show significant improvement in precision and an even bigger improvement in ...and semantic features into our neural models but they do not lead to improved perfor- ... See full document
6
Neural Semantic Role Labeling with Dependency Path Embeddings
... Dependency-based embeddings The idea of embedding dependency structures has previously been applied to tasks such as relation classifica- tion and sentiment analysis. Xu et al. (2015) and Liu et al. (2015) use ... See full document
11
Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling
... compared to an ensemble model (He et al., 2017) that has a higher overall F1. This is very likely due to architectural differences; in a BIO tagger, predicate information passes through many LSTM timesteps before ... See full document
6
Low Resource Semantic Role Labeling
... of semantic role labeling and predicate sense ...dependency syntax, (b) morphological features, (c) POS tags, and (d) ...Dependency syntax is the most expensive and difficult to obtain ... See full document
11
Semantic Role Labeling with Neural Network Factors
... On the WSJ development set (section 22), the la- beled attachment score of the parser is 90.9% while the part-of-speech tagger achieves an accuracy of 97.2%. On the CoNLL 2012 development set, the corresponding scores ... See full document
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Towards Robust Semantic Role Labeling
... The architecture just described has the drawback that each argument classification is made independently, without considering other arguments assigned to the same predicate. This ignores a potentially important source of ... See full document
22
An Argument Marker Model for Syntax Agnostic Proto Role Labeling
... end-to-end neural systems have been proposed (He et ...of syntax can help SRL models and Li et ...step, labeling their argument phrases with ... See full document
11
Improved Neural Machine Translation with a Syntax Aware Encoder and Decoder
... long-distance semantic dependencies mat- ter, representations learned from recursive mod- els using syntactic structures may be more pow- erful than those from sequential recurrent ... See full document
10
Sentence Simplification for Semantic Role Labeling
... the syntax as a set of local syntactic transfor- mations, is more linguistically satisfying than using the entire parse path as an atomic ...Second, labeling simple sentences is much easier than ... See full document
9
Towards Robust Semantic Role Labeling
... the syntax parse trees (Charniak) is heavily lexicalized and is trained on WSJ, it could have de- creased accuracy on the Brown data resulting in re- duced accuracy for Semantic Role ... See full document
8
Multi Predicate Semantic Role Labeling
... Sun and Jurafsky (2004) did the preliminary work on Chinese SRL without employing any large semantically annotated corpus of Chinese. They just labeled the predicate-argument struc- tures of ten specified verbs to a ... See full document
11
Tree Kernels for Semantic Role Labeling
... The availability of large scale data sets of manually annotated predicate–argument struc- tures has recently favored the use of machine learning approaches to the design of automated semantic role ... See full document
32
Collective Semantic Role Labeling on Open News Corpus by Leveraging Redundancy
... Table 1. Averaged 10-fold cross validation re- sults (Pre.: precision; Rec.: recall). Experimental results show that the two collec- tive inference engines (CI-1 and CI) perform significantly better than the baseline in ... See full document
5
End to end learning of semantic role labeling using recurrent neural networks
... Syntactic information is considered to play an essential role in solving this problem (Punyakanok et al., 2008a). The location of an argument on syn- tactic tree provides an intermediate tag for improv- ing the ... See full document
11
Semantic Parsing with Syntax and Table Aware SQL Generation
... Parsing. Semantic parsing aims to map natural language utterances to programs ...rameterized neural programmer (Yin et ...study semantic parsing over tables, which is critical for users to access ... See full document
12
Towards Syntax aware Compositional Distributional Semantic Models
... Compositional distributional semantics models (CDSMs) are functions mapping text fragments to vectors (or higher-order tensors). Functions for simple phrases directly map distributional vectors of words to distributional ... See full document
10
Syntax for Semantic Role Labeling, To Be, Or Not To Be
... deep neural net- works in various NLP tasks (Zhang et ...dependency semantic role labeler using convolutional and time-domain neural networks, while FitzGerald et ...ploited neural ... See full document
11
A Syntax aware Multi task Learning Framework for Chinese Semantic Role Labeling
... above syntax-free works, re- searchers also pay much attention on improving the neural-based SRL approaches by introducing syntactic ...the neural-based model and achieve substantial im- ... See full document
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