Papers by Shelby Anderson

2 papers
Dragonfly: Advances in Non-Speaker Annotation for Low Resource Languages (2020.lrec-1)

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Challenge: Using semantic and contextual information, non-speakers of a language familiar with the Latin script can produce high quality named entity annotations to support construction of . name tagger.
Approach: They propose a procedure for annotating low resource languages using Dragonfly that others can use.
Outcome: The proposed procedure improves the performance of NER models on native speaker and non-speaker annotations in low resource languages.
Tagging Location Phrases in Text (2020.lrec-1)

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Challenge: a number of studies have focused on detecting named entities in written language.
Approach: They describe a Location Phrase Detection task to detect non-named locations . they use sequential tagging and an annotation approach to create annotated datasets .
Outcome: The proposed task can detect non-named locations in English and Russian news . the authors develop a sequential tagging approach and annotate datasets for English and Russia .

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