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Zero-shot Neural Transfer for Cross-lingual Entity Linking [article]

Shruti Rijhwani and Jiateng Xie and Graham Neubig and Jaime Carbonell
2018 arXiv   pre-print
Cross-lingual entity linking maps an entity mention in a source language to its corresponding entry in a structured knowledge base that is in a different (target) language.  ...  Specifically, we propose pivot-based entity linking, which leverages information from a high-resource "pivot" language to train character-level neural entity linking models that are transferred to the  ...  Acknowledgements This work is sponsored by Defense Advanced Research Projects Agency Information Innovation Office (I2O), Program: Low Resource Languages for Emergent Incidents (LORELEI), issued by DARPA  ... 
arXiv:1811.04154v1 fatcat:zg6x27oo5zgbpokd6upjbskabm

Zero-Shot Neural Transfer for Cross-Lingual Entity Linking

Shruti Rijhwani, Jiateng Xie, Graham Neubig, Jaime Carbonell
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Cross-lingual entity linking maps an entity mention in a source language to its corresponding entry in a structured knowledge base that is in a different (target) language.  ...  To address this problem, we investigate zero-shot cross-lingual entity linking, in which we assume no bilingual lexical resources are available in the source low-resource language.  ...  Acknowledgements This work is sponsored by Defense Advanced Research Projects Agency Information Innovation Office (I2O), Program: Low Resource Languages for Emergent Incidents (LORELEI), issued by DARPA  ... 
doi:10.1609/aaai.v33i01.33016924 fatcat:b6eexla7tbe6hh4zo35i35acry

Design Challenges in Low-resource Cross-lingual Entity Linking [article]

Xingyu Fu, Weijia Shi, Xiaodong Yu, Zian Zhao, Dan Roth
2020 arXiv   pre-print
Cross-lingual Entity Linking (XEL), the problem of grounding mentions of entities in a foreign language text into an English knowledge base such as Wikipedia, has seen a lot of research in recent years  ...  With experiments on 25 languages, QuEL~shows an average increase of 25\% in gold candidate recall and of 13\% in end-to-end linking accuracy over state-of-the-art baselines.  ...  Introduction Cross-lingual Entity Linking (XEL) aims at grounding mentions written in a foreign (source) language (SL) into entries in a (target) language Knowledge Base (KB), which we consider here as  ... 
arXiv:2005.00692v2 fatcat:6y4nlajxjrdf3pn5hoxvipdspu

Towards Zero-resource Cross-lingual Entity Linking [article]

Shuyan Zhou and Shruti Rijhwani and Graham Neubig
2019 arXiv   pre-print
Cross-lingual entity linking (XEL) grounds named entities in a source language to an English Knowledge Base (KB), such as Wikipedia.  ...  Next, we propose three improvements to both entity candidate generation and disambiguation that make better use of the limited data we do have in resource-scarce scenarios.  ...  This material is based upon work supported in part by the Defense Advanced Research Projects Agency Information Innovation Office (I2O) Low Resource Languages for Emergent Incidents (LORELEI) program under  ... 
arXiv:1909.13180v2 fatcat:n5o52rygmbdz3jsbprxiicw3yi

Pivot Through English: Reliably Answering Multilingual Questions without Document Retrieval [article]

Ivan Montero, Shayne Longpre, Ni Lao, Andrew J. Frank, Christopher DuBois
2021 arXiv   pre-print
Existing methods for open-retrieval question answering in lower resource languages (LRLs) lag significantly behind English.  ...  They not only suffer from the shortcomings of non-English document retrieval, but are reliant on language-specific supervision for either the task or translation.  ...  We introduce and motivate the Cross-Lingual Pivots (XLP) task (Section 2), which we contend will For the Cross-Lingual Pivots task, we propose an approach that maps the LRL query to a semantically equivalent  ... 
arXiv:2012.14094v2 fatcat:bbvne32bxvhixowjyq5fewpxre

Improving Candidate Generation for Low-resource Cross-lingual Entity Linking [article]

Shuyan Zhou and Shruti Rijhwani and John Wieting and Jaime Carbonell and Graham Neubig
2020 arXiv   pre-print
Cross-lingual entity linking (XEL) is the task of finding referents in a target-language knowledge base (KB) for mentions extracted from source-language texts.  ...  The first step of (X)EL is candidate generation, which retrieves a list of plausible candidate entities from the target-language KB for each mention.  ...  This material is based upon work supported in part by the Defense Advanced Research Projects Agency Information Innovation Office (I2O) Low Resource Languages for Emergent Incidents (LORELEI) program under  ... 
arXiv:2003.01343v1 fatcat:mfwnsmnqy5elbbacl7v4e5o77e

Towards Zero-resource Cross-lingual Entity Linking

Shuyan Zhou, Shruti Rijhwani, Graham Neubig
2019 Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)  
Cross-lingual entity linking (XEL) grounds named entities in a source language to an English Knowledge Base (KB), such as Wikipedia.  ...  Next, we propose three improvements to both entity candidate generation and disambiguation that make better use of the limited data we do have in resource-scarce scenarios.  ...  This material is based upon work supported in part by the Defense Advanced Research Projects Agency Information Innovation Office (I2O) Low Resource Languages for Emergent Incidents (LORELEI) program under  ... 
doi:10.18653/v1/d19-6127 dblp:conf/acl-deeplo/ZhouRN19 fatcat:x3ada6rdxves3lpmm5nteaaiby

Soft Gazetteers for Low-Resource Named Entity Recognition [article]

Shruti Rijhwani, Shuyan Zhou, Graham Neubig, Jaime Carbonell
2020 arXiv   pre-print
models through cross-lingual entity linking.  ...  Although modern neural network models do not require such hand-crafted features for strong performance, recent work has demonstrated their utility for named entity recognition on English data.  ...  We also thank Samridhi Choudhary for help with the model implementation and Deepak Gopinath for feedback on the paper.  ... 
arXiv:2005.01866v1 fatcat:m43ofz2bhndgrbbl32rsy7vshm

Visual Pivoting for (Unsupervised) Entity Alignment [article]

Fangyu Liu, Muhao Chen, Dan Roth, Nigel Collier
2020 arXiv   pre-print
Experiments on benchmark data sets DBP15k and DWY15k show that EVA offers state-of-the-art performance on both monolingual and cross-lingual entity alignment tasks.  ...  By combining visual knowledge with other auxiliary information, we show that the proposed new approach, EVA, creates a holistic entity representation that provides strong signals for cross-graph entity  ...  Acknowledgement We appreciate the anonymous reviewers for their insightful comments and suggestions.  ... 
arXiv:2009.13603v2 fatcat:ryzlqkasijddpbezej76rb3uty

Introduction to the Special Issue on Cross-Language Algorithms and Applications

Marta R. Costa-jussà, Srinivas Bangalore, Patrik Lambert, Lluís Màrquez, Elena Montiel-Ponsoda
2016 The Journal of Artificial Intelligence Research  
development of the science of multi- and cross-lingualism.  ...  The selected papers cover a broad range of cross-lingual technologies including machine translation, domain and language adaptation for sentiment analysis, cross-language lexical resources, dependency  ...  Acknowledgements The authors want to thank Dan Roth, Mark Sammons and an anonymous reviewer for their useful comments and suggestions on previous versions of this document.  ... 
doi:10.1613/jair.5022 fatcat:h63kjmerufgkxh3qstvegklcyy

Neural Entity Linking: A Survey of Models Based on Deep Learning [article]

Ozge Sevgili, Artem Shelmanov, Mikhail Arkhipov, Alexander Panchenko, Chris Biemann
2021 arXiv   pre-print
techniques including zero-shot and distant supervision methods, and cross-lingual approaches.  ...  We distill generic architectural components of a neural EL system, like candidate generation and entity ranking, and summarize prominent methods for each of them.  ...  The work of Artem Shelmanov in the current study (preparation of sections related to application of entity linking to neural language models, entity ranking, contextmention encoding, and overall harmonization  ... 
arXiv:2006.00575v3 fatcat:ra3kwc4tmbfhlmgtlevkcshcqq

Neural entity linking: A survey of models based on deep learning

Özge Sevgili, Artem Shelmanov, Mikhail Arkhipov, Alexander Panchenko, Chris Biemann, Mehwish Alam, Davide Buscaldi, Michael Cochez, Francesco Osborne, Diego Reforgiato Recupero, Harald Sack
2022 Semantic Web Journal  
including zero-shot and distant supervision methods, and cross-lingual approaches.  ...  This work distills a generic architecture of a neural EL system and discusses its components, such as candidate generation, mention-context encoding, and entity ranking, summarizing prominent methods for  ...  The work of Artem Shelmanov in the current study (preparation of sections related to application of entity linking to neural language models, entity ranking, context-mention encoding, and overall harmonization  ... 
doi:10.3233/sw-222986 fatcat:6gwmbtev7ngbliovf6cpf5hyde

CLOUD BASED MULTI-LANGUAGE INDEXING USING CROSS LINGUAL INFORMATION RETRIEVAL APPROACHES

Chayapathi A R Et al.
2021 Information Technology in Industry  
To tackle such obstructions, CLIR, the cross-language information retrieval frameworks, are these days in solid interest.  ...  The options for distribution and parallelization of information in clouds make the retrieval and storage processes very complicated, especially when faced with real-time data management.  ...  Researchers in [2] also concentrated on Cross lingual information retrievalissues including named entities recognizing, dictionary-based problem, Out-Of-Vocabulary, and translation disambiguation.  ... 
doi:10.17762/itii.v9i1.269 fatcat:r5cge4dhsfbg3d5ei5gliisdpa

Cross-Lingual Adaptation using Structural Correspondence Learning [article]

Peter Prettenhofer, Benno Stein
2010 arXiv   pre-print
In this article we describe an extension of Structural Correspondence Learning (SCL), a recently proposed algorithm for domain adaptation, for cross-lingual adaptation.  ...  Cross-lingual adaptation, a special case of domain adaptation, refers to the transfer of classification knowledge between two languages.  ...  ., named entity recognition, relation extraction, sentiment analysis) and information retrieval (e.g., text classification, information filtering).  ... 
arXiv:1008.0716v2 fatcat:qygcn7nvuvea3erjgllg7vndlq

Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking [article]

Elliot Schumacher, James Mayfield, Mark Dredze
2021 arXiv   pre-print
Cross-language entity linking grounds mentions in multiple languages to a single-language knowledge base.  ...  We propose a neural ranking architecture for this task that uses multilingual BERT representations of the mention and the context in a neural network.  ...  Conclusion We demonstrate that a basic neural ranking architecture for cross-language entity linking can leverage the power of multilingual transformer representations to perform well on cross-lingual  ... 
arXiv:2010.09828v2 fatcat:yuck6j4ncrcllcikzmq7wlo2c4
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