Papers by Marcus Klang
Hedwig: A Named Entity Linker (2020.lrec-1)
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| Challenge: | Named entity linking is the task of identifying mentions of named things in text . e.g., "Barack Obama" or "New York" are examples of named entities . |
| Approach: | They propose an end-to-end named entity linker that uses BILSTM models for mention detection and a PageRank algorithm for entity linking. |
| Outcome: | The proposed named entity linker performs better than the previous generation, and is trilingually better. |
Linking, Searching, and Visualizing Entities in Wikipedia (L18-1)
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| Challenge: | Existing systems to extract, index, search, and visualize entities in Wikipedia are not strings, but unique identifiers from Wikidata. |
| Approach: | They propose a system to extract, index, search, and visualize entities in Wikipedia . they use a document model to store linguistic annotations and a string matching engine . |
| Outcome: | The proposed system achieves CEAFm scores of 70.0 on English, 64.4 on Chinese, and 66.5 on Spanish. |