# Text Annotation ## using Inception March 31st 2020 https://inception-project.github.io/ --- ## useful links <!-- Put the link to this slide here so people can follow --> * this presentation: https://hackmd.io/@ZwRJiT-YT3Ozt-Uoatu2Fg/ryL98_Jw8 * ENP's Inception: https://annotation.enpchina.eu/ * Inception user guide: https://inception-project.github.io/releases/0.14.3/docs/user-guide.html --- ## Text Annotation ### Why What and How ? (where :arrow_right: https://annotation.enp-china.eu/) ---- ## Why annotate ? * indexing * obtain statistics * train machine learning ---- ## What can be annotated ? ---- ### layers of annotation mostly linguistic or NLP related: * words * grammatical categories * Named Entities * Syntactic structures * Semantic relations * Discourse relations ---- ### formal object * text level * sentence level * span level * token level * relations --- ## How ? 1. Corpus selection / creation 2. Layer selection / creation 3. start annotation 4. with (semi-)automatic annotation ? Let's see in Inception ---- ### Corpus creation Important tabs * Users * Documents * Layers * Tagsets * Recommenders * Export (preferably in WebAnno TSV) ---- ### Annotation window * select a document * select a layer * start annotating * interact with recommenders --- # Possible Futures * import/export to/from R-Studio * integrated search (SolR) * Connect a Knowledge Base (Heurist) ---