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SBE-UKRI: From Manual to Automatic: Scaling Syntactic Annotation for Historical Language C — NSF Award to University of Pennsylvan

Annotated corpora -- texts marked up with information about grammatical structures -- are transforming how researchers study language change over time. However, the high cost of manual annotation has limited the size of these corpora and the research questions that can be asked. This project addresses this problem by b

Award titleSBE-UKRI: From Manual to Automatic: Scaling Syntactic Annotation for Historical Language C
Award ID2537480
AwardeeUniversity of Pennsylvania
CityPHILADELPHIA
StatePA
Amount obligated$399,970
Principal investigatorSeth Kulick
ProgramGVF - Global Venture Fund, Linguistics
Start date09/15/2025
AbstractAnnotated corpora -- texts marked up with information about grammatical structures -- are transforming how researchers study language change over time. However, the high cost of manual annotation has limited the size of these corpora and the research questions that can be asked. This project addresses this problem by building on and extending recent major advances in natural language processing (NLP) (a branch of artificial intelligence (AI)) to efficiently create very large collections (hundred
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