{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/bbw-matching-csv-to-wikidata-via-meta-lookup","title":"bbw: Matching CSV to Wikidata via Meta-lookup","arxiv_id":null,"date":"2021-03-01","proceeding":null,"authors":["Renat Shigapov","Philipp Zumstein","Jan Kamlah","Lars Oberländer","Jörg Mechnich","Irene Schumm"],"abstract":"We present our publicly available semantic annotator bbw (boosted by wiki) tested at the second Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab2020). It annotates a raw CSV-table using the entities, types and properties in Wikidata. Our key ideas are meta-lookup over the SearX metasearch API and contextual matching with at least two features. Avoiding the use of dump files, we kept the storage requirements low, used only up-to-date values in Wikidata and ranked third in the challenge.","url_abs":"https://drive.google.com/file/d/1b5sdsJfhXGGXP-xNj3xVu3ULH5tV4Nap/view","url_pdf":"https://drive.google.com/file/d/1b5sdsJfhXGGXP-xNj3xVu3ULH5tV4Nap/view","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"bbw-matching-csv-to-wikidata-via-meta-lookup","repo_url":"https://github.com/UB-Mannheim/bbw","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"entity-typing","task_name":"Entity Typing"},{"task_slug":"graph-matching","task_name":"Graph Matching"},{"task_slug":"named-entity-recognition-ner","task_name":"Named Entity Recognition (NER)"},{"task_slug":"relation-extraction","task_name":"Relation Extraction"},{"task_slug":"table-annotation","task_name":"Table annotation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}