Menghan Jiang


2020

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Edition 1.2 of the PARSEME Shared Task on Semi-supervised Identification of Verbal Multiword Expressions
Carlos Ramisch | Agata Savary | Bruno Guillaume | Jakub Waszczuk | Marie Candito | Ashwini Vaidya | Verginica Barbu Mititelu | Archna Bhatia | Uxoa Iñurrieta | Voula Giouli | Tunga Gungor | Menghan Jiang | Timm Lichte | Chaya Liebeskind | Johanna Monti | Renata Ramisch | Sara Stymne | Abigail Walsh | Hongzhi Xu
Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons

We present edition 1.2 of the PARSEME shared task on identification of verbal multiword expressions (VMWEs). Lessons learned from previous editions indicate that VMWEs have low ambiguity, and that the major challenge lies in identifying test instances never seen in the training data. Therefore, this edition focuses on unseen VMWEs. We have split annotated corpora so that the test corpora contain around 300 unseen VMWEs, and we provide non-annotated raw corpora to be used by complementary discovery methods. We released annotated and raw corpora in 14 languages, and this semi-supervised challenge attracted 7 teams who submitted 9 system results. This paper describes the effort of corpus creation, the task design, and the results obtained by the participating systems, especially their performance on unseen expressions.

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Using Conceptual Norms for Metaphor Detection
Mingyu Wan | Kathleen Ahrens | Emmanuele Chersoni | Menghan Jiang | Qi Su | Rong Xiang | Chu-Ren Huang
Proceedings of the Second Workshop on Figurative Language Processing

This paper reports a linguistically-enriched method of detecting token-level metaphors for the second shared task on Metaphor Detection. We participate in all four phases of competition with both datasets, i.e. Verbs and AllPOS on the VUA and the TOFEL datasets. We use the modality exclusivity and embodiment norms for constructing a conceptual representation of the nodes and the context. Our system obtains an F-score of 0.652 for the VUA Verbs track, which is 5% higher than the strong baselines. The experimental results across models and datasets indicate the salient contribution of using modality exclusivity and modality shift information for predicting metaphoricity.

2018

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Annotating Chinese Light Verb Constructions according to PARSEME guidelines
Menghan Jiang | Natalia Klyueva | Hongzhi Xu | Chu-Ren Huang
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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Lexicalization, Separation and transitivity: A comparative study of Mandarin VO compound Variations
Menghan Jiang | Chu-Ren Huang
Proceedings of the 31st Pacific Asia Conference on Language, Information and Computation

2016

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Transitivity in Light Verb Variations in Mandarin Chinese – A Comparable Corpus-based Statistical Approach
Menghan Jiang | Dingxu Shi | Chu-Ren Huang
Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation: Posters

2014

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Corpus-based Study and Identification of Mandarin Chinese Light Verb Variations
Chu-Ren Huang | Jingxia Lin | Menghan Jiang | Hongzhi Xu
Proceedings of the First Workshop on Applying NLP Tools to Similar Languages, Varieties and Dialects

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Annotation and Classification of Light Verbs and Light Verb Variations in Mandarin Chinese
Jingxia Lin | Hongzhi Xu | Menghan Jiang | Chu-Ren Huang
Proceedings of Workshop on Lexical and Grammatical Resources for Language Processing