BRISE-plandok: a German legal corpus of building regulations.
We present the BRISE-Plandok corpus, a collection of 250 text documents with a total of over 7000 sentences from the Zoning Map of the City of Vienna, annotated manually with formal representations of the rules they convey. The generic rule format used by the corpus enables automated compliance chec...
| Publicado en: | Language Resources & Evaluation Vol. 59; no. 2; pp. 1043 - 1083 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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Springer Nature
Jun2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=185240042&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 185240042 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Jun2025 vid: 59 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 185240042 10.1007/s10579-024-09747-7 ppf: 1043 ppct: 40 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2.1MB tig: atl: BRISE-plandok: a German legal corpus of building regulations. aug: au: Recski, Gábor Iklódi, Eszter Lellmann, Björn Kovács, Ádám Hanbury, Allan affil: https://ror.org/04d836q62 TU Wien, Vienna, Austria Federal Ministry of Finance, Vienna, Austria https://ror.org/02w42ss30 Budapest University of Technology and Economics, Budapest, Hungary https://ror.org/023dz9m50 Complexity Science Hub, Vienna, Austria su: Machine learning Image processing software Building inspection Artificial intelligence Zoning Deontic logic sug: subj: Machine learning Image processing software Building inspection Artificial intelligence Zoning Deontic logic keyword: Annotation, Automated compliance checking Information and Computing Sciences Artificial Intelligence and Image Processing Computer Software Rule corpus Rule extraction Rule-based methods ab: We present the BRISE-Plandok corpus, a collection of 250 text documents with a total of over 7000 sentences from the Zoning Map of the City of Vienna, annotated manually with formal representations of the rules they convey. The generic rule format used by the corpus enables automated compliance checking of building plans, a process developed as part of the BRISE (https://smartcity.wien.gv.at/en/brise/) project. The format also allows for conversion to multiple logic formalisms, including dyadic deontic logic, enabling automated reasoning. Annotation guidelines were developed in collaboration with experts of the city's building inspection office, describing nearly 100 domain-specific attributes with examples. Each document was annotated independently by two trained annotators and subsequently reviewed by the authors. A rule-based system for the automatic extraction of rules from text was developed and used in the annotation process to provide suggestions. The reviewed dataset was also used to train a set of baseline machine learning models for the task of attribute extraction, the main step in the rule extraction process. Both the rule-based system and the ML baselines are evaluated on the annotated dataset and released as open-source software. We also describe and release the framework used for generating and parsing the interactive xlsx spreadsheets used by annotators. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2025. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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