Transforming Wikipedia into a Large-Scale Fine-Grained Entity Type Corpus (L18-1)
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| Challenge: | et al. (2017): WiFiNE annotated with fine-grained entity types . lack of a well-established training corpus makes it difficult to manually annotate the amount of data needed for training. |
| Approach: | They propose an English corpus annotated with fine-grained entity types based on Wikipedia . they use heuristics to build a large, high quality, annotating corpus using 2 manually annotized benchmarks . |
| Outcome: | The proposed system outperforms the existing systems with two datasets and gains a 2.8 macro F1 score. |
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| Challenge: | Existing approaches to fine-grained entity typing are limited by the errors in the annotation process. |
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