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Chinese Relation Extraction with Multi-Grained Information and External Linguistic Knowledge
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
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To address the issues, we propose a multi-grained lattice framework (MG lattice) for Chinese relation extraction to take advantage of multi-grained language information and external linguistic knowledge ...
Chinese relation extraction is conducted using neural networks with either character-based or word-based inputs, and most existing methods typically suffer from segmentation errors and ambiguity of polysemy ...
In this paper, we proposed the multi-granularity lattice framework (MG lattice), a unified model comprehensively utilizes both internal information and external knowledge, to conduct the Chinese RE task ...
doi:10.18653/v1/p19-1430
dblp:conf/acl/LiDLZS19
fatcat:jxp5llwmknbx7f67jovaf6ebne
Learning Fine-grained Fact-Article Correspondence in Legal Cases
[article]
2021
arXiv
pre-print
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We treat the learning as a text matching task and propose a multi-level matching network to address it. ...
Furthermore, we compare with previous researches and find that establishing the fine-grained fact-article correspondences can improve the recommendation accuracy by a large margin. ...
and the external knowledge of law articles Q. ...
arXiv:2104.10726v3
fatcat:o2ht6u6bifezffvy6nbkxyctrm
Lexicon-Enhanced Multi-Task Convolutional Neural Network for Emotion Distribution Learning
2022
Axioms
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The LMT-CNN model designs an end-to-end multi-module deep neural network to utilize both semantic information and linguistic knowledge. ...
Specifically, the architecture of the LMT-CNN model consists of a semantic information module, an emotion knowledge module based on affective words, and a multi-task prediction module to predict emotion ...
In contrast, deep learning algorithms can automate feature extraction, which allows researchers to extract features with minimal domain knowledge and manpower. ...
doi:10.3390/axioms11040181
fatcat:slpbpbkvizctdjw5zqhstogsi4
Toward Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning
[article]
2020
arXiv
pre-print
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Multi-criteria Chinese word segmentation aims to capture various annotation criteria among datasets and leverage their common underlying knowledge. ...
Private and shared projection layers are proposed to capture domain-specific knowledge and common knowledge, respectively. ...
., 2018; pointed out that exploiting external knowledge can improve the CWS accuracy. ...
arXiv:1903.04190v2
fatcat:g5hhis3vajdyznv4wphhrqgaju
Background Knowledge Based Multi-Stream Neural Network for Text Classification
2018
Applied Sciences
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Background knowledge is composed of keywords and co-occurred words which are extracted from external corpus. ...
The multi-stream network mainly consists of the basal stream, which retained original sequence information, and background knowledge based streams. ...
The background knowledge is extracted from external corpus and is composed of keywords and co-occurred words. ...
doi:10.3390/app8122472
fatcat:3zt2mcwomvgx7bmxisyyuvy7uy
Auxiliary Signal-Guided Knowledge Encoder-Decoder for Medical Report Generation
[article]
2020
arXiv
pre-print
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In more detail, ASGK integrates internal visual feature fusion and external medical linguistic information to guide medical knowledge transfer and learning. ...
Beyond the common difficulties faced in the natural image captioning, medical report generation specifically requires the model to describe a medical image with a fine-grained and semantic-coherence paragraph ...
model to bridge visual and linguistic information. ...
arXiv:2006.03744v1
fatcat:3nwchs5irffyvlxyba4vkiajmu
Cross-lingual Name Tagging and Linking for 282 Languages
2017
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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Given a document in any of these languages, our framework is able to identify name mentions, assign a coarse-grained or fine-grained type to each mention, and link it to an English Knowledge Base (KB) ...
Both name tagging and linking results for 282 languages are promising on Wikipedia data and on-Wikipedia data. ...
FA8750-13-2-0041 and FA8750-13-2-0045, and NSF CAREER No. IIS-1523198. ...
doi:10.18653/v1/p17-1178
dblp:conf/acl/PanZMNKJ17
fatcat:sdo4vpvxk5haxkql3554v4alqa
Extracting event and their relations from texts: A survey on recent research progress and challenges
2020
AI Open
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This paper summaries some constructed event-centric knowledge graphs and the recent typical approaches for event and event relation extraction, besides task description, widely used evaluation datasets ...
In event relation extraction, we focus on the extraction approaches for three typical event relation types, including coreference, causal and temporal relations, respectively. ...
Priority Research Program of Chinese Academy of Sciences (Grant No. ...
doi:10.1016/j.aiopen.2021.02.004
fatcat:qxbcmk55vzcb5nznhgfgwrbe4u
TravelBERT: Pre-training Language Model Incorporating Domain-specific Heterogeneous Knowledge into A Unified Representation
[article]
2021
arXiv
pre-print
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To capture the corresponding relations among these multi-format knowledge, our approach uses masked language model objective to learn word knowledge, uses triple classification objective and title matching ...
objective to learn entity knowledge and topic knowledge respectively. ...
For the TravelOIE dataset, the data annotation relies on the information extraction mechanism of dependency parsing (Qiu and Zhang, 2014 ), but we did not specifically add linguistic knowledge during ...
arXiv:2109.01048v2
fatcat:eaegcialtrbtdjuqxl46nuwedm
LOME: Large Ontology Multilingual Extraction
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2101.12175v1 fatcat:mofr7zqed5drflqizspsosbhp4
By doing so, the system constructs an event and entity focused knowledge graph. We can further apply third-party modules for other types of annotation, like relation extraction. ...
It subsequently performs coreference resolution, fine-grained entity typing, and temporal relation prediction between events. ...
Acknowledgments We thank Kenton Murray, Manling Li, Varun Iyer, and Zhuowan Li for helpful discussions and feedback. ...
arXiv:2101.12175v2
fatcat:aviegtknb5hb5kf5eysd5qdili
Neural relation extraction: a review
2020
Turkish Journal of Electrical Engineering and Computer Sciences
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external knowledge bases are used to enhance 21 weakly labeled training set. ...
A triple (h, r , t ) implies that entity h has relation r with another entity t . Knowledge graphs (KG) 18 such as FreeBase [4] and DBpedia [2] are examples of such representations. ...
., and Li, P. (2018b). Hierarchical relation extraction with coarse-to-fine grained 40 attention. ...
doi:10.3906/elk-2005-119
fatcat:o36duadbunhmbesuyayc5jfmxe
Linguistically Annotated Reordering: Evaluation and Analysis
2010
Computational Linguistics
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When combined with BWR, LAR provides complementary information for phrase reordering, which collectively improves the BLEU score significantly. ...
In LAR, we build hard hierarchical skeletons and inject soft linguistic knowledge from source parse trees to nodes of hard skeletons during translation. ...
Acknowledgments We would like to thank the three anonymous reviewers for their helpful comments and suggestions. ...
doi:10.1162/coli_a_00009
fatcat:kzn6ydkakzecparatgjgtcnyfq
A Survey of Implicit Discourse Relation Recognition
[article]
2022
arXiv
pre-print
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The task of implicit discourse relation recognition (IDRR) is to detect implicit relation and classify its sense between two text segments without a connective. ...
We also present performance comparisons for those solutions experimented on a public corpus with standard data processing procedures. ...
Ji and Eisenstein [41] proposed to further augment a tree-structured RNN with external entity mentions and some other linguistically informed features, like word-pair feature, to enrich input words' ...
arXiv:2203.02982v1
fatcat:ubublxw2fnfdpexgw4jslj76tm
Enhancing Topic-to-Essay Generation with External Commonsense Knowledge
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
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Experiments show that with external commonsense knowledge and adversarial training, the generated essays are more novel, diverse, and topic-consistent than existing methods in terms of both automatic and ...
However, this commonsense knowledge provides additional background information, which can help to generate essays that are more novel and diverse. ...
This shows that with the help of external commonsense knowledge, the source information can be enriched, leading to the outputs that are more novel and diverse. ...
doi:10.18653/v1/p19-1193
dblp:conf/acl/YangLLLS19
fatcat:pa3msr4qezgm3or7ocegzcl44u
BERT Based Chinese Relation Extraction for Public Security
2020
IEEE Access
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With the advent of the big data era, effectively extracting public security information from the internet has become of great significance. ...
Therefore, in this paper, we propose a Bidirectional Encoder Representation from Transformers (BERT) based on the Chinese relation extraction algorithm for public security, which can effectively mine security ...
ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their helpful feedback and suggestions. ...
doi:10.1109/access.2020.3002863
fatcat:6kolwgcalzar3insvgn43e2heu
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