Erik Tjong Kim Sang

Also published as: Erik F. Tjong Kim Sang


2020

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Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media
Shihan Wang | Marijn Schraagen | Erik Tjong Kim Sang | Mehdi Dastani
Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020

Public sentiment (the opinion, attitude or feeling that the public expresses) is a factor of interest for government, as it directly influences the implementation of policies. Given the unprecedented nature of the COVID-19 crisis, having an up-to-date representation of public sentiment on governmental measures and announcements is crucial. In this paper, we analyse Dutch public sentiment on governmental COVID-19 measures from text data collected across three online media sources (Twitter, Reddit and Nu.nl) from February to September 2020. We apply sentiment analysis methods to analyse polarity over time, as well as to identify stance towards two specific pandemic policies regarding social distancing and wearing face masks. The presented preliminary results provide valuable insights into the narratives shown in vast social media text data, which help understand the influence of COVID-19 measures on the general public.

2016

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Nederlab: Towards a Single Portal and Research Environment for Diachronic Dutch Text Corpora
Hennie Brugman | Martin Reynaert | Nicoline van der Sijs | René van Stipriaan | Erik Tjong Kim Sang | Antal van den Bosch
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The Nederlab project aims to bring together all digitized texts relevant to the Dutch national heritage, the history of the Dutch language and culture (circa 800 – present) in one user friendly and tool enriched open access web interface. This paper describes Nederlab halfway through the project period and discusses the collections incorporated, back-office processes, system back-end as well as the Nederlab Research Portal end-user web application.

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Finding Rising and Falling Words
Erik Tjong Kim Sang
Proceedings of the Workshop on Language Technology Resources and Tools for Digital Humanities (LT4DH)

We examine two different methods for finding rising words (among which neologisms) and falling words (among which archaisms) in decades of magazine texts (millions of words) and in years of tweets (billions of words): one based on correlation coefficients of relative frequencies and time, and one based on comparing initial and final word frequencies of time intervals. We find that smoothing frequency scores improves the precision scores of both methods and that the correlation coefficients perform better on magazine text but worse on tweets. Since the two ranking methods find different words they can be used in side-by-side to study the behavior of words over time.

2012

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Predicting the 2011 Dutch Senate Election Results with Twitter
Erik Tjong Kim Sang | Johan Bos
Proceedings of the Workshop on Semantic Analysis in Social Media

2010

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A Baseline Approach for Detecting Sentences Containing Uncertainty
Erik Tjong Kim Sang
Proceedings of the Fourteenth Conference on Computational Natural Language Learning – Shared Task

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GikiCLEF: Crosscultural Issues in Multilingual Information Access
Diana Santos | Luís Miguel Cabral | Corina Forascu | Pamela Forner | Fredric Gey | Katrin Lamm | Thomas Mandl | Petya Osenova | Anselmo Peñas | Álvaro Rodrigo | Julia Schulz | Yvonne Skalban | Erik Tjong Kim Sang
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

In this paper we describe GikiCLEF, the first evaluation contest that, to our knowledge, was specifically designed to expose and investigate cultural and linguistic issues involved in structured multimedia collections and searching, and which was organized under the scope of CLEF 2009. GikiCLEF evaluated systems that answered hard questions for both human and machine, in ten different Wikipedia collections, namely Bulgarian, Dutch, English, German, Italian, Norwegian (Bokmäl and Nynorsk), Portuguese, Romanian, and Spanish. After a short historical introduction, we present the task, together with its motivation, and discuss how the topics were chosen. Then we provide another description from the point of view of the participants. Before disclosing their results, we introduce the SIGA management system explaining the several tasks which were carried out behind the scenes. We quantify in turn the GIRA resource, offered to the community for training and further evaluating systems with the help of the 50 topics gathered and the solutions identified. We end the paper with a critical discussion of what was learned, advancing possible ways to reuse the data.

2009

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Lexical Patterns or Dependency Patterns: Which Is Better for Hypernym Extraction?
Erik Tjong Kim Sang | Katja Hofmann
Proceedings of the Thirteenth Conference on Computational Natural Language Learning (CoNLL-2009)

2007

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A Constraint Satisfaction Approach to Dependency Parsing
Sander Canisius | Erik Tjong Kim Sang
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

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Extracting Hypernym Pairs from the Web
Erik Tjong Kim Sang
Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions

2006

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Dependency Parsing by Inference over High-recall Dependency Predictions
Sander Canisius | Toine Bogers | Antal van den Bosch | Jeroen Geertzen | Erik Tjong Kim Sang
Proceedings of the Tenth Conference on Computational Natural Language Learning (CoNLL-X)

2005

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Applying Spelling Error Correction Techniques for Improving Semantic Role Labelling
Erik Tjong Kim Sang | Sander Canisius | Antal van den Bosch | Toine Bogers
Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005)

2004

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Memory-based semantic role labeling: Optimizing features, algorithm, and output
Antal van den Bosch | Sander Canisius | Walter Daelemans | Iris Hendrickx | Erik Tjong Kim Sang
Proceedings of the Eighth Conference on Computational Natural Language Learning (CoNLL-2004) at HLT-NAACL 2004

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Using a Parallel Transcript/Subtitle Corpus for Sentence Compression
Vincent Vandeghinste | Erik Tjong Kim Sang
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Automatic Sentence Simplification for Subtitling in Dutch and English
Walter Daelemans | Anja Höthker | Erik Tjong Kim Sang
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

2003

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Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition
Erik F. Tjong Kim Sang | Fien De Meulder
Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003

2002

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Introduction to the CoNLL-2002 Shared Task: Language-Independent Named Entity Recognition
Erik F. Tjong Kim Sang
COLING-02: The 6th Conference on Natural Language Learning 2002 (CoNLL-2002)

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Memory-Based Named Entity Recognition
Erik F. Tjong Kim Sang
COLING-02: The 6th Conference on Natural Language Learning 2002 (CoNLL-2002)

2001

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Combining a self-organising map with memory-based learning
James Hammerton | Erik F. Tjong Kim Sang
Proceedings of the ACL 2001 Workshop on Computational Natural Language Learning (ConLL)

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Introduction to the CoNLL-2001 shared task: clause identification
Erik F. Tjong Kim Sang | Hervé Déjean
Proceedings of the ACL 2001 Workshop on Computational Natural Language Learning (ConLL)

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Learning Computational Grammars
John Nerbonne | Anja Belz | Nicola Cancedda | Hervé Déjean | James Hammerton | Rob Koeling | Stasinos Konstantopoulos | Miles Osborne | Franck Thollard | Erik F. Tjong Kim Sang
Proceedings of the ACL 2001 Workshop on Computational Natural Language Learning (ConLL)

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Memory-based clause identification
Erik F. Tjong Kim Sang
Proceedings of the ACL 2001 Workshop on Computational Natural Language Learning (ConLL)

2000

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Applying System Combination to Base Noun Phrase Identification
Erik F. Tjong Kim Sang | Walter Daelemans | Herve Dejean | Rob Koeling | Yuval Krymolowski | Vasin Punyakanok | Dan Roth
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

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Noun Phrase Recognition by System Combination
Erik F. Tjong Kim Sang
1st Meeting of the North American Chapter of the Association for Computational Linguistics

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Introduction to the CoNLL-2000 Shared Task Chunking
Erik F. Tjong Kim Sang | Sabine Buchholz
Fourth Conference on Computational Natural Language Learning and the Second Learning Language in Logic Workshop

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Text Chunking by System Combination
Erik F. Tjong Kim Sang
Fourth Conference on Computational Natural Language Learning and the Second Learning Language in Logic Workshop

1999

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Representing Text Chunks
Erik F. Tjong Kim Sang | Jorn Veenstra
Ninth Conference of the European Chapter of the Association for Computational Linguistics

1998

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CATCH: A Program for Developing World Wide Web CALL Material
Erik F. Tjong Kim Sang
Proceedings of the 11th Nordic Conference of Computational Linguistics (NODALIDA 1998)