Nadin Kökciyan

Also published as: Nadin Kokciyan


2023

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Uncovering Implicit Inferences for Improved Relational Argument Mining
Ameer Saadat-Yazdi | Jeff Z. Pan | Nadin Kokciyan
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

Argument mining seeks to extract arguments and their structure from unstructured texts. Identifying relations between arguments (such as attack, support, and neutral) is a challenging task because two arguments may be related to each other via implicit inferences. This task often requires external commonsense knowledge to discover how one argument relates to another. State-of-the-art methods, however, rely on pre-defined knowledge graphs, and thus might not cover target argument pairs well. We introduce a new generative neuro-symbolic approach to finding inference chains that connect the argument pairs by making use of the Commonsense Transformer (COMET). We evaluate our approach on three datasets for both the two-label (attack/support) and three-label (attack/support/neutral) tasks. Our approach significantly outperforms the state-of-the-art, by 2-5% in F1 score, on all three datasets.

2022

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KEViN: A Knowledge Enhanced Validity and Novelty Classifier for Arguments
Ameer Saadat-Yazdi | Xue Li | Sandrine Chausson | Vaishak Belle | Björn Ross | Jeff Z. Pan | Nadin Kökciyan
Proceedings of the 9th Workshop on Argument Mining

The ArgMining 2022 Shared Task is concerned with predicting the validity and novelty of an inference for a given premise and conclusion pair. We propose two feed-forward network based models (KEViN1 and KEViN2), which combine features generated from several pretrained transformers and the WikiData knowledge graph. The transformers are used to predict entailment and semantic similarity, while WikiData is used to provide a semantic measure between concepts in the premise-conclusion pair. Our proposed models show significant improvement over RoBERTa, with KEViN1 outperforming KEViN2 and obtaining second rank on both subtasks (A and B) of the ArgMining 2022 Shared Task.

2013

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BOUNCE: Sentiment Classification in Twitter using Rich Feature Sets
Nadin Kökciyan | Arda Çelebi | Arzucan Özgür | Suzan Üsküdarlı
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)