{"type":"ScholarlyArticle","title":"TimeML-Compliant Text Analysis for Temporal Reasoning","authors":[{"name":"Branimir Boguraev","slug":"branimir-boguraev","given":"Branimir","family":"Boguraev","affiliation":""},{"name":"Rie Kubota Ando","slug":"rie-kubota-ando","given":"Rie Kubota","family":"Ando","affiliation":""}],"abstract":"Reasoning with time 1 needs more than just a list of temporal expressions. T ime ML —an emerging standard for temporal annotation as a language capturing properties and relationships among timedenoting expressions and events in text—is a good starting point for bridging the gap between temporal analysis of documents and reasoning with the information derived from them. Hard as T ime MLcompliant analysis is, the small size of the only currently available annotated corpus makes it even harder. We address this problem with a hybrid T ime ML annotator, which uses cascaded finite-state grammars (for temporal expression analysis, shallow syntactic parsing, and feature generation) together with a machine learning component capable of effectively using large amounts of unannotated data.","doi":null,"url":"https://ijcai.org/proceedings/2005/142","pdf":"https://ijcai.org/proceedings/2005/0142.pdf","markdown":"https://ijcai.org/proceedings/2005/142.md","bibtex":"https://ijcai.org/proceedings/2005/bibtex/142","volume":{"slug":"2005","title":"Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2005","url":"https://ijcai.org/proceedings/2005/","year":2005,"location":"Edinburgh, Scotland, UK","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":142,"pages":{"first":997,"last":1002},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}