Papers by Enfa George
Generating Uncontextualized and Contextualized Questions for Document-Level Event Argument Extraction (2024.naacl-long)
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| Challenge: | Existing methods for document-level argument extraction do not require human involvement and combine uncontextualized and contextualized questions. |
| Approach: | They propose multiple question generation strategies for document-level event argument extraction that do not require human involvement and combine uncontextualized and contextualized questions. |
| Outcome: | The proposed questions do not require human involvement and are suitable for document-level argument extraction. |
It’s not Sexually Suggestive; It’s Educative | Separating Sex Education from Suggestive Content on TikTok videos (2023.findings-acl)
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| Challenge: | Existing systems for TikTok remove/punish both types of videos, even though they serve different purposes. |
| Approach: | They propose a dataset that contains TikTok videos labeled as sexually suggestive, sex-educational content, or neither . they explore two transformer-based models for classifying the videos to validate their importance . |
| Outcome: | The proposed dataset is useful and invites further study on the subject. |
Extracting Space Situational Awareness Events from News Text (2022.lrec-1)
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Zhengnan Xie, Alice Saebom Kwak, Enfa George, Laura W. Dozal, Hoang Van, Moriba Jah, Roberto Furfaro, Peter Jansen
| Challenge: | Space situational awareness is the decisionmaking knowledge required to predict, avoid, operate through, or recover from the loss, disruption, or degradation of space services, capabilities, or activities. |
| Approach: | They construct a corpus of 48.5k news articles spanning all known active satellites between 2009 and 2020 that are annotated by humans with 15.9k labels for event slots. |
| Outcome: | The proposed system achieves an overall F1 between 53 and 91 per slot for event extraction in this low-resource, high-impact domain. |