Papers with Automatic Content Extraction
When ACE met KBP: End-to-End Evaluation of Knowledge Base Population with Component-level Annotation (L18-1)
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| Challenge: | Automating constructing a Knowledge Base from unstructured text is a goal of natural language processing. |
| Approach: | They propose a method to evaluate a Knowledge Base population from unstructured text . they propose bootstrap resampling to provide statistical significance to the results . |
| Outcome: | The proposed method uses component-level annotations to evaluate Cold Start KBP . it also uses bootstrap resampling to provide statistical significance to the results reported . |
Evaluating Zero-Shot Event Structures: Recommendations for Automatic Content Extraction (ACE) Annotations (2023.acl-short)
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| Challenge: | Zero-shot event extraction (EE) methods infer richly structured event records from unstructured text data, based on a user-supplied natural language specification and no training examples. |
| Approach: | They propose recommendations for future evaluations so the research community can better utilize ACE as an event evaluation resource. |
| Outcome: | The proposed methods can be used to evaluate zero-shot and other low-supervision EE methods, considering up to 32% of correctly identified arguments and 25% of correctly ignored event mentions as false negatives. |
Extracting Financial Events from Raw Texts via Matrix Chunking (2024.lrec-main)
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| Challenge: | Event Extraction (EE) is widely used in the Chinese financial field to provide valuable structured information. |
| Approach: | They propose a task which extracts financial events from raw texts and an efficient method called MACK. |
| Outcome: | The proposed method is fault-tolerant and can visualize interactions among text components. |