A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
A joint syntactic and semantic dependency parsing system based on maximum entropy models
2009
Proceedings of the Thirteenth Conference on Computational Natural Language Learning Shared Task - CoNLL '09
unpublished
Preserved Fulltext
A joint syntactic and semantic dependency parsing system submitted to the CoNLL-2009 shared task is presented in this paper. ...
Predicate classification and semantic parsing are both recognized as classification problem, and the Maximum Entropy Models are used for them in our system. ...
This research has been partially supported by the National Natural Science Foundation of China(No.60703015) and the National 863 Program of China (No.2006AA01Z197, No.2007AA01Z194). ...
doi:10.3115/1596409.1596428
fatcat:mlxlwopiuffdnmmwhtak3f6uay
Hybrid learning of Syntactic and Semantic Dependencies
2010
Computer and Information Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2010; you can also visit the original URL.
The file type is application/pdf.
This paper presents our solution for jointly parsing of syntactic and semantic dependencies. The Maximum Entropy (ME) classifier is selected in this system. ...
Also the Mutual Information (MI) model was utilized into feature selection of dependency labeling. Results show that the MI model allows the system to get better performance and reduce training hours. ...
System Architecture: Comparing with traditional Semantic Role Label, our system will produce a joint rich syntactic-semantic output to allow people getting semantic role annotation and syntactic structure ...
doi:10.5539/cis.v3n4p187
fatcat:pu5fdjrud5cmnpz22zm2v65k54
Using semantic analysis to improve speech recognition performance
2005
Computer Speech and Language
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2006; you can also visit the original URL.
The file type is application/pdf.
These models also differ in how the lexical and semantic information is combined, ranging from simple interpolation to tight integration using maximum entropy modeling. ...
We call these methods concept sequence modeling, two-level semantic-lexical modeling, and joint semantic-lexical modeling. ...
Acknowledgements The authors thank Adwait Ratnaparkhi for the use of his code implementing maximum entropy training and testing algorithms and Mike Monkowski for designing grammars in the financial domain ...
doi:10.1016/j.csl.2004.10.002
fatcat:swilwbulpjgqloma5g2lhol43i
ICT: A System Combination for Chinese Semantic Dependency Parsing
2012
International Workshop on Semantic Evaluation
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The goal of semantic dependency parsing is to build dependency structure and label semantic relation between a head and its modifier. ...
To attain this goal, we concentrate on obtaining better dependency structure to predict better semantic relations, and propose a method to combine the results of three state-of-the-art dependency parsers ...
We thank Heng Yu for generating parse tree using Liang's algorithm. We thank organizers for their generous supplied resources and arduous preparation. ...
dblp:conf/semeval/XiongL12
fatcat:j65o3ojaj5a4pk2c6mdyhvtihu
Semantic Role Labeling Based on Dependency Tree with Multi-features
2009
2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2012; you can also visit the original URL.
The file type is application/pdf.
In this paper, a dependency tree-based semantic role labeling (SRL) system is proposed. ...
Firstly, this paper introduces current SRL research situation, analyses syntactic tree-based SRL and dependency tree-based SRL comparatively. ...
We would also like to thank our referees for their helpful comments and suggestions. ...
doi:10.1109/ijcbs.2009.99
dblp:conf/ijcbs/ShiZQL09
fatcat:wcrcd67mnjfbfd4mnh4iwgyiju
English Syntactic Analysis and Word Sense Disambiguation Strategy of Neutral Set from the Perspective of Natural Language Processing
2022
Advances in Multimedia
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
set and solves the parameters through data training, so as to solve the probability distribution of the maximum entropy model of each order. ...
Moreover, by comparing the prediction probability of the model to the judgment mode with the experimental data, it is found that the first-order maximum entropy model (independent model) is quite different ...
Acknowledgments is study was sponsored by Zhengzhou Railway Vocational and Technical College. ...
doi:10.1155/2022/4421976
fatcat:dg27qo632ja6de7i5jyocc2cui
A Survey of Syntactic-Semantic Parsing Based on Constituent and Dependency Structures
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Syntactic and semantic parsing has been investigated for decades, which is one primary topic in the natural language processing community. This article aims for a brief survey on this topic. ...
Constituent parsing is majorly targeted to syntactic analysis, and dependency parsing can handle both syntactic and semantic analysis. ...
Acknowledgments This work is supported by National Natural Science Foundation of China (NSFC) grants 61602160 and 61672211. ...
arXiv:2006.11056v1
fatcat:pd22rciuxzdc5kvghaapjjyg3u
Joint Syntactic and Semantic Parsing of Chinese
2010
Annual Meeting of the Association for Computational Linguistics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This paper explores joint syntactic and semantic parsing of Chinese to further improve the performance of both syntactic and semantic parsing, in particular the performance of semantic parsing (in this ...
Moreover, it shows that incorporating semantic role-related information into the syntactic parsing model significantly improves the performance of both syntactic parsing and semantic parsing. ...
This research was also partially supported by a research grant R-252-000-225-112 from National University of Singapore Academic Research Fund. ...
dblp:conf/acl/LiZN10
fatcat:x7gxfbeohzgztmv33ewp3yomaq
Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this work, we propose a transition sampling algorithm to sample from the full joint distribution of parse trees defined by a transition-based parsing model, and demonstrate the use of the samples in ...
First, we define the new task of dependency path prediction, inferring syntactic substructures over part of a sentence, and provide the first analysis of performance on this task. ...
It would be interesting to modify the sampler to restrict to parses that are consistent with the span, as a form of rejection sampling. ...
arXiv:1804.06004v1
fatcat:r3nhbyvohjcfzplllrghibzibm
Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses
2018
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this work, we propose a transition sampling algorithm to sample from the full joint distribution of parse trees defined by a transition-based parsing model, and demonstrate the use of the samples in ...
First, we define the new task of dependency path prediction, inferring syntactic substructures over part of a sentence, and provide the first analysis of performance on this task. ...
Acknowledgments The authors would like to thank Rajarshi Das, Daniel Cohen, Abe Handler, Graham Neubig, Emma Strubell, and the anonymous reviewers for their helpful comments. ...
doi:10.18653/v1/n18-1084
dblp:conf/naacl/KeithBO18
fatcat:3sptkvng5ravfeuebzhu5avu2m
Page 190 of Computational Linguistics Vol. 34, Issue 2
[page]
2008
Computational Linguistics
Preserved Fulltext
The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
Gildea, Daniel and Daniel Jurafsky. 2002 Automatic labeling of semantic roles. Computational Linguistics, 28(3):245-288.
Hacioglu, Kadri. 2004. A lightweight semantic chunking model based on tagging. ...
Haghighi, Aria, Kristina Toutanova, and Christopher D. Manning. 2005. A joint model for semantic role labeling. In Proceedings of CoNLL, pages 173-176, Ann Arbor, MI. ...
Parsing All: Syntax and Semantics, Dependencies and Spans
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this paper, we propose a novel joint model of syntactic and semantic parsing on both span and dependency representations, which incorporates syntactic information effectively in the encoder of neural ...
Our single model achieves new state-of-the-art or competitive results on both span and dependency semantic parsing on Propbank benchmarks and both dependency and constituent syntactic parsing on Penn Treebank ...
Since we convert two syntactic representations as joint span structure and apply uniform semantic representation, we only need two decoders, one for syntactic tree based on joint span syntactic parsing ...
arXiv:1908.11522v3
fatcat:4dmcw5gybvfmldfnrj6i7elsou
What a Parser Can Learn from a Semantic Role Labeler and Vice Versa
2010
Conference on Empirical Methods in Natural Language Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This process relies on an averaged perceptron model to distinguish likely semantic roles from erroneous ones. Our system penalizes parses that give rise to low-scoring semantic roles. ...
First, we use a baseline generative model to produce n-best parses, which are then re-ordered by our semantic model. ...
Acknowledgements We would like to thank Mike White, William Schuler, Eric Fosler-Lussier, and Matthew Honnibal for their helpful feedback. ...
dblp:conf/emnlp/BoxwellMB10
fatcat:ul2nh4ywavhwvopfwzogtl4jyu
Joint semantic utterance classification and slot filling with recursive neural networks
2014
2014 IEEE Spoken Language Technology Workshop (SLT)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
We find that a very simple RecNN model achieves competitive performance on the benchmark ATIS task, as well as on a Microsoft Cortana conversational understanding task. ...
In this paper, we show that RecNNs can be used to perform the core spoken language understanding (SLU) tasks in a spoken dialog system, more specifically domain and intent determination, concurrently with ...
The setting we choose is similar to the standard multi-class maximum entropy model. ...
doi:10.1109/slt.2014.7078634
dblp:conf/slt/GuoTYZ14
fatcat:pi4f3u4skbafhckhlh6f72sixa
Page 548 of Computational Linguistics Vol. 33, Issue 4
[page]
2007
Computational Linguistics
Preserved Fulltext
The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
A quasi- arithmetical notation for syntactic description. Language, 29:47-58.
Borthwick, Andrew. 1999. A Maximum Entropy Approach to Named Entity Recognition. ...
In Proceedings of IWPT
2000, Trento, Italy
C hen, Stanley and Ronald Rosenfeld. 1999. A Gaussian prior for smoothing maximum entropy models. ...
« Previous
Showing results 1 — 15 out of 2,396 results