Papers by Ghazaleh Kazeminejad
A Graphical Interface for Curating Schemas (2021.acl-demo)
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| Challenge: | Existing work on analyzing information extracted from documents has focused on examining the model understanding of complex schemas. |
| Approach: | They propose a curation interface that takes an IE system’s output in a pre-defined format and generates a graphical representation of its elements. |
| Outcome: | The proposed interface can be used to edit and prune schemas for complex events like Improvised Explosive Device (IED) based scenarios. |
RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios (2022.naacl-demo)
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Xinya Du, Zixuan Zhang, Sha Li, Pengfei Yu, Hongwei Wang, Tuan Lai, Xudong Lin, Ziqi Wang, Iris Liu, Ben Zhou, Haoyang Wen, Manling Li, Darryl Hannan, Jie Lei, Hyounghun Kim, Rotem Dror, Haoyu Wang, Michael Regan, Qi Zeng, Qing Lyu, Charles Yu, Carl Edwards, Xiaomeng Jin, Yizhu Jiao, Ghazaleh Kazeminejad, Zhenhailong Wang, Chris Callison-Burch, Mohit Bansal, Carl Vondrick, Jiawei Han, Dan Roth, Shih-Fu Chang, Martha Palmer, Heng Ji
| Challenge: | Existing methods for event prediction are incomplete and noisy. |
| Approach: | They propose to use news-related event schemas to extract newsworthy events . they build a demo website and include a video demonstrating the framework . |
| Outcome: | The proposed framework can be applied to a wide variety of newsworthy scenarios. |
Learning Semantic Role Labeling from Compatible Label Sequences (2023.findings-emnlp)
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| Challenge: | Prior work has shown that cross-task interaction helps, but only explored multitask learning so far. |
| Approach: | They propose a framework that jointly models VerbNet and PropBank labels as one sequence and enforcing Semlink constraints during decoding improves the overall F1 . |
| Outcome: | The proposed model outperforms the prior best in-domain model by 3.5 (VerbNet) and 0.8 (PropBank). |
Event Semantic Knowledge in Procedural Text Understanding (2023.starsem-1)
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| Challenge: | Annotators’ reliance on commonsense knowledge to annotate implicit state information is a challenge for entity state tracking. |
| Approach: | They propose a method for entity state tracking that incorporates commonsense entity-centric knowledge from ConceptNet into a BERT-based neural-symbolic architecture. |
| Outcome: | The proposed model outperforms existing models on the ProPara dataset and is domain-agnostic. |
Automatically Extracting Qualia Relations for the Rich Event Ontology (C18-1)
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| Challenge: | a new study uses qualia relations extracted from the Suggested Upper Merged Ontology to extract information about entities . human annotators find qualia relationships and origins of the information to be reasonable . |
| Approach: | They propose to extract qualia from the Generative Lexicon to extract quealia . they assume the theoretical framework of the Generative Lexicons . |
| Outcome: | The proposed method extracts information from the Suggested Upper Merged Ontology (SUMO) human annotators find the extracted information to be reasonable, the authors show . |