[PDF] Top 20 Neural Semantic Role Labeling with Dependency Path Embeddings
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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 ...use neural networks to embed de- ... See full document
11
Syntax-Aware Neural Semantic Role Labeling
... hance neural network based SRL approaches by ...tagging, dependency parsing, and SRL to obtain better encoding of the input ...other semantic-related tasks such as SRL and coreference ...on ... See full document
9
Dependency or Span, End-to-End Uniform Semantic Role Labeling
... into neural networks with embedded lexicalized features, while Roth and Lapata (2016) embedded syntactic dependency paths between pred- icates and ...multi-task neural model to incorporate auxiliary ... See full document
8
A Shortest path Method for Arc factored Semantic Role Labeling
... over dependency arcs— is supported by some empirical ...frequent path patterns on CoNLL- 2009 (Hajiˇc et ...a path pattern is a sequence of as- cending arcs from the predicate to some ancestor, ... See full document
6
Combining Constituent and Dependency Syntactic Views for Chinese Semantic Role Labeling
... categories except LOC, in which the combina- tion of the new feature 'locational cue words' (c27) and the 'voice (c5)' feature performs the best. The results also show that the most fre- quently occurred basic features ... See full document
9
Facing the most difficult case of Semantic Role Labeling: A collaboration of word embeddings and co training
... Recently, there has been interest in distributional word representations for natural language processing. Such representations are typically learned from a large corpus using neural networks (e.g., Weston et al. ... See full document
10
Semantic Role Labeling with Neural Network Factors
... the dependency-based CoNLL 2009 shared task by assuming single word argument spans, that rep- resent semantic dependencies, and limit our ex- periments to ... See full document
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Evaluating semantic relations in neural word embeddings with biomedical and general domain knowledge bases
... The dependency-based word embeddings had the worse performance among the ...word embeddings may vary across different domains and differ- ent text ...word embeddings using stan- dard ... See full document
16
Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling
... ELMo embeddings To further improve perfor- mance, we also add ELMo word representations (Peters et ...vious neural systems, the improvement is orthog- onal to our ... See full document
6
Neural Models of Selectional Preferences for Implicit Semantic Role Labeling
... target role with as input: the predicate, the role and, if applicable, other explicit ...pretrained embeddings of Collobert et ...in neural networks, we run each model 15 times and average the ... See full document
6
Syntax for Semantic Role Labeling, To Be, Or Not To Be
... deep neural net- works in various NLP tasks (Zhang et ...a dependency semantic role labeler using convolutional and time-domain neural networks, while FitzGerald et ...ploited ... See full document
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A Simple and Accurate Syntax Agnostic Neural Model for Dependency based Semantic Role Labeling
... 2005). Neural SRL models instead ex- ploited feature induction capabilities of neural net- works, largely eliminating the need for complex hand-crafted ...2009), neural SRL models now also outperform ... See full document
10
Dependency Parsing and Semantic Role Labeling as a Single Task
... Results of Classifiers 1 and 3 indicate that learn- ing the tasks jointly produces a moderately better performance. The results of the main classifier, C1, show that syntactic and semantic dependencies are better ... See full document
6
Chinese Semantic Role Labeling with Bidirectional Recurrent Neural Networks
... tic Role Labeling (SRL) almost heavily re- ly on feature ...recurrent neural network (RNN) with long-short-term memory (LSTM) to cap- ture bidirectional and long-range depen- dencies in a sentence ... See full document
6
Brutus: A Semantic Role Labeling System Incorporating CCG, CFG, and Dependency Features
... As in previous approaches to SRL, Brutus uses a two- stage pipeline of maximum entropy classifiers. In ad- dition, we train an argument mapping classifier (de- scribed in more detail below) whose predictions are used as ... See full document
9
Comparing Semantic Role Labeling with Typed Dependency Parsing in Computational Metaphor Identification
... using semantic role labeling (SRL) in ...that semantic roles can effectively be used to identify conceptual metaphors, and second, to compare SRL to the current use of typed dependency ... See full document
9
Parsing Chinese Sentences with Grammatical Relations
... a dependency representation has been well studied and widely applied to many Natural Language Processing (NLP) tasks, for example, Information Extraction and Machine ... See full document
42
Enhancing Active Learning for Semantic Role Labeling via Compressed Dependency Trees
... on semantic similar- ity (Haghighi et ...the dependency tree instead of semantic/lexical sim- ilarity of the ...collapsed dependency relations to calculate the semantic similarity of ... See full document
9
Polyglot Semantic Role Labeling
... mantic dependency parsing treat lan- guages independently, without exploiting the similarities between semantic struc- tures across ...polyglot semantic role la- ... See full document
6
Grounded Semantic Role Labeling
... the semantic frame for each ...of dependency parsing ...each semantic role (including both explicit roles and implicit roles) of a given verb, we also annotated the ground truth grounding in ... See full document
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