dependency tree
Discovery of Dependency Tree Patterns for Relation Extraction
... Our algorithm proposed in this paper belongs to the rules learning framework. The reason we choose the rule-based method is that the rules could contain more semantic information than features used in statistical ...
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Dependency Tree Kernels for Relation Extraction
... a dependency tree ker- nel for relation extraction provides a vast improve- ment over a bag-of-words ...pendency tree kernel appears to perform well at the task of classifying relations, recall is ...
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Flexible Non Terminals for Dependency Tree to Tree Reordering
... for dependency tree-to-tree reorder- ing based on flexible non-terminals that can compactly encode multiple insertion ...strong tree-to-tree ...
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Go Climb a Dependency Tree and Correct the Grammatical Errors
... We propose a TreeNode Language Model (TNLM) to efficiently measure the correctness of selecting a correction candidate of a node in the general module. Similar to the existing statistical language models which assign a ...
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EasyTree: A Graphical Tool for Dependency Tree Annotation
... and-drop. As depicted in Figure 3, when the user begins dragging a node, red circles appear around the remaining nodes. These “drop zones” indicate where the node may be re-attached. When the dragged node is eventually ...
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Dependency Tree Annotation with Mechanical Turk
... for dependency tree annotation using workers who are presumably non-experts, demonstrating the potential value that non-experts can bring to parsing annotation ...
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BinLin: A Simple Method of Dependency Tree Linearization
... 2002), tree linearization using probabilistic language mod- els (Guo et ...full tree linearization and (3) partial tree linearization (Liu et ...full tree linearization case, since the ...
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Experiments with Generative Models for Dependency Tree Linearization
... els. Dependency tree nodes are labeled with word- forms, lemmas, and parts-of-speech (POS) tags; and dependency tree edges are labeled with rela- tion ...for dependency linearization, ...
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Dependency Tree Transformation with Tree Transducers
... a tree transducer are ranked. A node in a dependency tree can have any number of children, therefore the alphabet in the tree can be assumed to contain each symbol with multiple different ...
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Czech English Dependency Tree based Machine Translation
... The fully auto- mated process includes: morphological tagging, analytical and tectogrammat- ical parsing of Czech, tectogrammati- cal transfer based on lexical substitu- tion using word-[r] ...
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Sentence Compression For Automatic Subtitling
... The first approach is to prune the dependency trees of the sentences. The goal of this approach is to produce more syntactically valid output than re- ducing the sentence based on its linear order. This, however, ...
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Head First Linearization with Tree Structured Representation
... a dependency tree linearization model with two novel components: (1) a tree-structured encoder based on bidirectional Tree-LSTM that propagates information first bottom-up then top-down, which ...
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K Best Spanning Tree Dependency Parsing With Verb Valency Lexicon Reranking
... validating dependency relations with respect to valency ...a dependency tree as input. It searches the tree for verbal ...the tree score is incremented. The final score of the ...
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Language Independent Dependency to Constituent Tree Conversion
... simple dependency to constituent tree conversion technique which is applicable to any languages and any dependencies, ...Universal Dependency (UD), CoNLL de- pendencies (CoNLL), Stanford dependencies ...
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Transformation and Decomposition for Efficiently Implementing and Improving Dependency to String Model In Moses
... Furthermore, we enhance the model by de- composing head-dependent fragments into smaller pieces. This decomposition enriches the Dep2Str model with more rules during training and allows us to create a pseudo-forest as ...
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Do we need phrases? Challenging the conventional wisdom in Statistical Machine Translation
... In this paper, we address all four theoretical problems using a novel combination of our syntactically-informed treelet approach (Quirk and Menezes 2005) and a modified version of bilingual n-gram channel models (Banchs ...
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Online Learning of Approximate Dependency Parsing Algorithms
... treating dependency parsing as the search for the highest scoring maximum spanning tree (MST) in a graph yields efficient algorithms for both projective and non-projective ...a dependency tree ...
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Compositional Semantic Parsing across Graphbanks
... dency tree from a graph, that dependency tree eval- uates uniquely to the original ...AM dependency tree in the way described ...
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Weighted posets: Learning surface order from dependency trees
... Figure 2: Overview of methodology. (a) A CoNLL-U file is parsed by word2vecf to produce (b) a list of syntactic word embeddings for each wordform|POS|relation, POS|relation, and POS. These embeddings form the node ...
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Extracting Narrative Timelines as Temporal Dependency Structures
... poral dependency structures, where each event is a node in the dependency tree, and each edge between nodes represents a temporal ordering relation such as BEFORE , AFTER , OVERLAP or IDENTITY ...
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