[PDF] Top 20 Parsing the WSJ Using CCG and Log Linear Models
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Parsing the WSJ Using CCG and Log Linear Models
... Following Clark et al. (2002), evaluation is by precision and recall over dependencies. For a la- belled dependency to be correct, the first 4 elements of the dependency tuple must match exactly. For an unlabelled ... See full document
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Wide Coverage Efficient Statistical Parsing with CCG and Log Linear Models
... of CCG has implications for the engineering of a wide- coverage ...to parsing can produce an extremely efficient ...almost parsing. The parser is able to parse 20 Wall Street Journal ( WSJ ) ... See full document
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Log Linear Models for Wide Coverage CCG Parsing
... Log-linear models have previously been ap- plied to statistical parsing (Johnson et al., 1999; Toutanova et al., 2002; Riezler et al., 2002; Os- borne, 2000). Typically, these approaches have ... See full document
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Object Extraction and Question Parsing using CCG
... parsers using Combinatory Categorial Grammar ( CCG ...a CCG parser on ob- ject extraction dependencies found in WSJ ...only. Using a supertagger to assign categories to words, trained ... See full document
8
A Virtual Manipulative for Learning Log Linear Models
... Log-linear models can be also used for struc- tured prediction problems in NLP such as tagging, parsing, chunking, segmentation, and language ...conditional log-linear model ... See full document
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LSTM CCG Parsing
... joint CCG and SRL model (Lewis et al., 2015) to CCGbank parsing, by assigning every CCGbank dependency a role based on its argument number ...global log-linear model is trained to maximize the ... See full document
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Minimum Risk Annealing for Training Log Linear Models
... training log-linear combinations of models for dependency parsing and for machine translation ( § ...Training Log-Linear ... See full document
8
Log Linear Models of Non Projective Trees, k best MST Parsing and Tree Ranking
... We present our system used in the CoNLL 2007 shared task on multilingual parsing. The system is composed of three compo- nents: a k-best maximum spanning tree (MST) parser, a tree labeler, and a reranker that ... See full document
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LSTM Shift-Reduce CCG Parsing
... a CCG derivation ...in CCG (Hockenmaier, 2003; Clark and Curran, 2007), and in line with most ex- isting CCG parsing models, including dependency models, we have chosen to model ... See full document
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Shift Reduce CCG Parsing using Neural Network Models
... of CCG parsers are chart-based (Clark and Curran, 2007; Lewis and Steedman, 2014a), there has been some work on shift-reduce CCG pars- ing (Zhang and Clark, 2011; Xu et ...global linear model trained ... See full document
7
Utilizing Extra Sentential Context for Parsing
... the WSJ portion of the Penn Tree- bank, and show that syntactic consistency is pervasive across productions with various left- hand side ...set. Using a linear-chain conditional random field, we ... See full document
11
Transfer Learning for Constituency Based Grammars
... There have been several attempts to map anno- tations in coarse grammars like CFG to annota- tions in richer grammar, like HPSG, LFG, or CCG. Traditional approaches in this area typically rely on manually ... See full document
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Semantic Parsing with Structured SVM Ensemble Classification Models
... Beside that, forming committees or ensembles of learned systems is known to improve accuracy and bagging and boosting are two popular ensem- ble methods that typically achieve better accuracy than a single classifier ... See full document
8
A* CCG Parsing with a Supertag factored Model
... parse CCG optimally and efficiently, without using excessive ...existing CCG parsers rely on aggres- sive pruning—for example, the C&C parser uses a supertagger to dramatically cut the search ... See full document
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Parsing Noun Phrase Structure with CCG
... In addition, we have made possible further in- creases to NP structure accuracy. New features can now be implemented and evaluated in a CCG pars- ing context. For example, bigram counts from a very large corpus ... See full document
9
Head Driven Parsing for Word Lattices
... mized using a memory and processor profiler and debugger. Parsing the complete set of HUB-1 lat- tices (213 sentences, a total of 3,446 words) on av- erage takes approximately 8 hours, on an Intel Pen- tium ... See full document
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Unsupervised Morphological Segmentation with Log Linear Models
... learning using mono- lingual features only (S&B-MONO-S), and for su- pervised bilingual learning with labels for both lan- guages ...our log-linear model is better suited to take advantage of ... See full document
9
Structured Penalties for Log Linear Language Models
... norms (Zhao et al., 2009; Jenatton et al., 2011). Structured penalties have been successfully applied to various NLP tasks, including chunking and named entity recognition (Martins et al., 2011), but not lan- guage ... See full document
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Supertagging With LSTMs
... are a natural and powerful architecture for CCG su- pertagging. In addition to the bi–LSTM, we create a simple yet novel model that outperforms the pre- vious state-of-the-art RNN model that uses hand- crafted ... See full document
6
A Comparison Of The Output Of Three Econometric Models In Evaluating The Relationship Between Taxes And Economic Growth In Nigeria.
... econometric models different from functional, mathematical or statistical ...on linear function, equation 8 on translog function and equation 11 on log quadratic ... See full document
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