Papers by Kathryn Conger
GLEN: General-Purpose Event Detection for Thousands of Types (2023.emnlp-main)
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| Challenge: | ACE 2005 2 is the first large-scale event extraction dataset with 205K event mentions and 3,465 different types. |
| Approach: | They propose to use the DWD Overlay to map PropBank rolesets to a large distantlysupervised training dataset with partial labels to make event extraction more accessible. |
| Outcome: | The proposed model performs better than baselines including InstructGPT and ACE 2005 2 despite being 18 years old . key limitations of ACE include its small event ontology of 33 types, small dataset size of around 600 documents and restricted domain (with a significant portion concentrated on military conflicts). |
NewsClaims: A New Benchmark for Claim Detection from News with Attribute Knowledge (2022.emnlp-main)
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Revanth Gangi Reddy, Sai Chetan Chinthakindi, Zhenhailong Wang, Yi Fung, Kathryn Conger, Ahmed ELsayed, Martha Palmer, Preslav Nakov, Eduard Hovy, Kevin Small, Heng Ji
| Challenge: | Current claims detection methods focus on sentence analysis, ignoring other attributes . a key element of identifying misinformation is detecting the claims and the arguments that have been presented. |
| Approach: | They propose a benchmark for attribute-aware claim detection in the news domain . they extend the problem to include extraction of additional attributes related to each claim . |
| Outcome: | The proposed system performs well on the test, but human performance is still poor. |
PropBank Comes of Age—Larger, Smarter, and more Diverse (2022.starsem-1)
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Sameer Pradhan, Julia Bonn, Skatje Myers, Kathryn Conger, Tim O’gorman, James Gung, Kristin Wright-bettner, Martha Palmer
| Challenge: | The PropBank has been used for semantic role labeling for over 20 years . it includes non-verbal predicates, adjectives, prepositions and multi-word expressions . |
| Approach: | They describe the evolution of the PropBank approach to semantic role labeling over the last 20 years . they describe the substantial effort that has gone into ensuring consistency and reliability of the various annotated datasets and resources . |
| Outcome: | The PropBank has been used for more than 20 years to test semantic role labeling systems. |
The Russian PropBank (2020.lrec-1)
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| Challenge: | Using proposition bank for Russian, we can automatically project semantic role labels from English to Russian. |
| Approach: | They propose a proposition bank for Russian that automatically projects semantic role labels from English to Russian. |
| Outcome: | The proposed resource automatically projectes semantic role labels from English to Russian. |