An Algorithm that Learns What‘s in a Name
Machine Learning - Special issue on natural language learning
A hybrid approach for named entity and sub-type tagging
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Information extraction from voicemail
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Using machine learning to maintain rule-based named-entity recognition and classification systems
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Information extraction from voicemail transcripts
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
The common pattern specification language
TIPSTER '98 Proceedings of a workshop on held at Baltimore, Maryland: October 13-15, 1998
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Maximum entropy models for named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Named entity recognition through classifier combination
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Factorizing complex models: a case study in mention detection
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Extracting personal names from email: applying named entity recognition to informal text
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Exploiting domain structure for named entity recognition
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Declarative information extraction using datalog with embedded extraction predicates
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
On the provenance of non-answers to queries over extracted data
Proceedings of the VLDB Endowment
Provenance in Databases: Why, How, and Where
Foundations and Trends in Databases
Domain adaptation with structural correspondence learning
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Regular expression learning for information extraction
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
Context and Domain Knowledge Enhanced Entity Spotting in Informal Text
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Nested named entity recognition
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Domain adaptive bootstrapping for named entity recognition
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Minimally-supervised extraction of entities from text advertisements
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
SystemT: an algebraic approach to declarative information extraction
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Automatic rule refinement for information extraction
Proceedings of the VLDB Endowment
ESpotter: adaptive named entity recognition for web browsing
WM'05 Proceedings of the Third Biennial conference on Professional Knowledge Management
The SystemT IDE: an integrated development environment for information extraction rules
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
SystemT: a declarative information extraction system
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
Recognizing named entities in tweets
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Training a named entity recognizer on the web
WISE'11 Proceedings of the 12th international conference on Web information system engineering
Facilitating pattern discovery for relation extraction with semantic-signature-based clustering
Proceedings of the 20th ACM international conference on Information and knowledge management
Automatic identification of protagonist in fairy tales using verb
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
VAHA: verbs associate with human activity --- a study on fairy tales
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
WizIE: a best practices guided development environment for information extraction
ACL '12 Proceedings of the ACL 2012 System Demonstrations
Joint inference of named entity recognition and normalization for tweets
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Towards efficient named-entity rule induction for customizability
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Two-stage NER for tweets with clustering
Information Processing and Management: an International Journal
Named entity recognition for tweets
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Provenance-based dictionary refinement in information extraction
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Person attribute extraction from the textual parts of web pages
Acta Cybernetica
Deterministic coreference resolution based on entity-centric, precision-ranked rules
Computational Linguistics
| Hi-index | 0.00 |
Named-entity recognition (NER) is an important task required in a wide variety of applications. While rule-based systems are appealing due to their well-known "explainability," most, if not all, state-of-the-art results for NER tasks are based on machine learning techniques. Motivated by these results, we explore the following natural question in this paper: Are rule-based systems still a viable approach to named-entity recognition? Specifically, we have designed and implemented a high-level language NERL on top of SystemT, a general-purpose algebraic information extraction system. NERL is tuned to the needs of NER tasks and simplifies the process of building, understanding, and customizing complex rule-based named-entity annotators. We show that these customized annotators match or outperform the best published results achieved with machine learning techniques. These results confirm that we can reap the benefits of rule-based extractors' explainability without sacrificing accuracy. We conclude by discussing lessons learned while building and customizing complex rule-based annotators and outlining several research directions towards facilitating rule development.