Jong-Hoon Oh

Also published as: Jong Hoon Oh


2019

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Event Causality Recognition Exploiting Multiple Annotators’ Judgments and Background Knowledge
Kazuma Kadowaki | Ryu Iida | Kentaro Torisawa | Jong-Hoon Oh | Julien Kloetzer
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

We propose new BERT-based methods for recognizing event causality such as “smoke cigarettes” –> “die of lung cancer” written in web texts. In our methods, we grasp each annotator’s policy by training multiple classifiers, each of which predicts the labels given by a single annotator, and combine the resulting classifiers’ outputs to predict the final labels determined by majority vote. Furthermore, we investigate the effect of supplying background knowledge to our classifiers. Since BERT models are pre-trained with a large corpus, some sort of background knowledge for event causality may be learned during pre-training. Our experiments with a Japanese dataset suggest that this is actually the case: Performance improved when we pre-trained the BERT models with web texts containing a large number of event causalities instead of Wikipedia articles or randomly sampled web texts. However, this effect was limited. Therefore, we further improved performance by simply adding texts related to an input causality candidate as background knowledge to the input of the BERT models. We believe these findings indicate a promising future research direction.

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Open-Domain Why-Question Answering with Adversarial Learning to Encode Answer Texts
Jong-Hoon Oh | Kazuma Kadowaki | Julien Kloetzer | Ryu Iida | Kentaro Torisawa
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

In this paper, we propose a method for why-question answering (why-QA) that uses an adversarial learning framework. Existing why-QA methods retrieve “answer passages” that usually consist of several sentences. These multi-sentence passages contain not only the reason sought by a why-question and its connection to the why-question, but also redundant and/or unrelated parts. We use our proposed “Adversarial networks for Generating compact-answer Representation” (AGR) to generate from a passage a vector representation of the non-redundant reason sought by a why-question and exploit the representation for judging whether the passage actually answers the why-question. Through a series of experiments using Japanese why-QA datasets, we show that these representations improve the performance of our why-QA neural model as well as that of a BERT-based why-QA model. We show that they also improve a state-of-the-art distantly supervised open-domain QA (DS-QA) method on publicly available English datasets, even though the target task is not a why-QA.

2016

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Intra-Sentential Subject Zero Anaphora Resolution using Multi-Column Convolutional Neural Network
Ryu Iida | Kentaro Torisawa | Jong-Hoon Oh | Canasai Kruengkrai | Julien Kloetzer
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

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WISDOM X, DISAANA and D-SUMM: Large-scale NLP Systems for Analyzing Textual Big Data
Junta Mizuno | Masahiro Tanaka | Kiyonori Ohtake | Jong-Hoon Oh | Julien Kloetzer | Chikara Hashimoto | Kentaro Torisawa
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations

We demonstrate our large-scale NLP systems: WISDOM X, DISAANA, and D-SUMM. WISDOM X provides numerous possible answers including unpredictable ones to widely diverse natural language questions to provide deep insights about a broad range of issues. DISAANA and D-SUMM enable us to assess the damage caused by large-scale disasters in real time using Twitter as an information source.

2015

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Large-Scale Acquisition of Entailment Pattern Pairs by Exploiting Transitivity
Julien Kloetzer | Kentaro Torisawa | Chikara Hashimoto | Jong-Hoon Oh
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

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Intra-sentential Zero Anaphora Resolution using Subject Sharing Recognition
Ryu Iida | Kentaro Torisawa | Chikara Hashimoto | Jong-Hoon Oh | Julien Kloetzer
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

2014

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Toward Future Scenario Generation: Extracting Event Causality Exploiting Semantic Relation, Context, and Association Features
Chikara Hashimoto | Kentaro Torisawa | Julien Kloetzer | Motoki Sano | István Varga | Jong-Hoon Oh | Yutaka Kidawara
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Million-scale Derivation of Semantic Relations from a Manually Constructed Predicate Taxonomy
Motoki Sano | Kentaro Torisawa | Julien Kloetzer | Chikara Hashimoto | István Varga | Jong-Hoon Oh
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

2013

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Two-Stage Method for Large-Scale Acquisition of Contradiction Pattern Pairs using Entailment
Julien Kloetzer | Stijn De Saeger | Kentaro Torisawa | Chikara Hashimoto | Jong-Hoon Oh | Motoki Sano | Kiyonori Ohtake
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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Aid is Out There: Looking for Help from Tweets during a Large Scale Disaster
István Varga | Motoki Sano | Kentaro Torisawa | Chikara Hashimoto | Kiyonori Ohtake | Takao Kawai | Jong-Hoon Oh | Stijn De Saeger
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Why-Question Answering using Intra- and Inter-Sentential Causal Relations
Jong-Hoon Oh | Kentaro Torisawa | Chikara Hashimoto | Motoki Sano | Stijn De Saeger | Kiyonori Ohtake
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2012

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Why Question Answering using Sentiment Analysis and Word Classes
Jong-Hoon Oh | Kentaro Torisawa | Chikara Hashimoto | Takuya Kawada | Stijn De Saeger | Jun’ichi Kazama | Yiou Wang
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

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Excitatory or Inhibitory: A New Semantic Orientation Extracts Contradiction and Causality from the Web
Chikara Hashimoto | Kentaro Torisawa | Stijn De Saeger | Jong-Hoon Oh | Jun’ichi Kazama
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

2011

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Relation Acquisition using Word Classes and Partial Patterns
Stijn De Saeger | Kentaro Torisawa | Masaaki Tsuchida | Jun’ichi Kazama | Chikara Hashimoto | Ichiro Yamada | Jong Hoon Oh | Istvan Varga | Yulan Yan
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

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Extending WordNet with Hypernyms and Siblings Acquired from Wikipedia
Ichiro Yamada | Jong-Hoon Oh | Chikara Hashimoto | Kentaro Torisawa | Jun’ichi Kazama | Stijn De Saeger | Takuya Kawada
Proceedings of 5th International Joint Conference on Natural Language Processing

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Toward Finding Semantic Relations not Written in a Single Sentence: An Inference Method using Auto-Discovered Rules
Masaaki Tsuchida | Kentaro Torisawa | Stijn De Saeger | Jong-Hoon Oh | Jun’ichi Kazama | Chikara Hashimoto | Hayato Ohwada
Proceedings of 5th International Joint Conference on Natural Language Processing

2010

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Co-STAR: A Co-training Style Algorithm for Hyponymy Relation Acquisition from Structured and Unstructured Text
Jong-Hoon Oh | Ichiro Yamada | Kentaro Torisawa | Stijn De Saeger
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)

2009

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Can Chinese Phonemes Improve Machine Transliteration?: A Comparative Study of English-to-Chinese Transliteration Models
Jong-Hoon Oh | Kiyotaka Uchimoto | Kentaro Torisawa
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing

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Machine Transliteration using Target-Language Grapheme and Phoneme: Multi-engine Transliteration Approach
Jong-Hoon Oh | Kiyotaka Uchimoto | Kentaro Torisawa
Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration (NEWS 2009)

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Bilingual Co-Training for Monolingual Hyponymy-Relation Acquisition
Jong-Hoon Oh | Kiyotaka Uchimoto | Kentaro Torisawa
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP

2008

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Hypothesis Selection in Machine Transliteration: A Web Mining Approach
Jong-Hoon Oh | Hitoshi Isahara
Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-I

2005

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An Ensemble of Grapheme and Phoneme for Machine Transliteration
Jong-Hoon Oh | Key-Sun Choi
Second International Joint Conference on Natural Language Processing: Full Papers

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Automatic Extraction of English-Korean Translations for Constituents of Technical Terms
Jong-Hoon Oh | Key-Sun Choi
Companion Volume to the Proceedings of Conference including Posters/Demos and tutorial abstracts

2002

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Word Sense Disambiguation with Information Retrieval Technique
Jong-Hoon Oh | Saim Shin | Yong-Seok Choi | Key-Sun Choi
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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Word Sense Disambiguation using Static and Dynamic Sense Vectors
Jong-Hoon Oh | Key-Sun Choi
COLING 2002: The 19th International Conference on Computational Linguistics

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An English-Korean Transliteration Model Using Pronunciation and Contextual Rules
Jong-Hoon Oh | Key-Sun Choi
COLING 2002: The 19th International Conference on Computational Linguistics

2000

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Term Recognition Using Technical Dictionary Hierarchy
Jong-Hoon Oh | KyungSoon Lee | Key-Sun Choi
Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics