{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T18:55:22Z","timestamp":1761418522743},"reference-count":5,"publisher":"World Scientific Pub Co Pte Lt","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Semantic Computing"],"published-print":{"date-parts":[[2007,12]]},"abstract":"<jats:p> This research proposes and evaluates a linguistically motivated approach to extracting temporal structure from text. Pairs of events in a verb-clause construction were considered, where the first event is a verb and the second event is the head of a clausal argument to that verb. All pairs of events in the TimeBank that participated in verb-clause constructions were selected and annotated with the labels BEFORE, OVERLAP and AFTER. The resulting corpus of 895 event-event temporal relations was then used to train a machine learning model. Using a combination of event-level features like tense and aspect with syntax-level features like the paths through the syntactic tree, support vector machine (SVM) models were trained which could identify new temporal relations with 89.2% accuracy. High accuracy models like these are a first step towards automatic extraction of temporal structure from text. <\/jats:p>","DOI":"10.1142\/s1793351x07000238","type":"journal-article","created":{"date-parts":[[2008,4,9]],"date-time":"2008-04-09T09:44:44Z","timestamp":1207734284000},"page":"441-457","source":"Crossref","is-referenced-by-count":7,"title":["FINDING TEMPORAL STRUCTURE IN TEXT: MACHINE LEARNING OF SYNTACTIC TEMPORAL RELATIONS"],"prefix":"10.1142","volume":"01","author":[{"given":"STEVEN","family":"BETHARD","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Colorado at Boulder, 430 UCB, Boulder, CO 80309, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JAMES H.","family":"MARTIN","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Colorado at Boulder, 430 UCB, Boulder, CO 80309, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"SARA","family":"KLINGENSTEIN","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Colorado at Boulder, 430 UCB, Boulder, CO 80309, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2012,1,25]]},"reference":[{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-005-0912-2"},{"key":"rf7","unstructured":"James\u00a0Pustejovsky, Corpus Linguistics (2003)\u00a0pp. 647\u2013656."},{"key":"rf9","series-title":"Dagstuhl Seminars","volume-title":"Annotating, Extracting and Reasoning about Time and Events","author":"Boguraev Branimir","year":"2005"},{"key":"rf14","first-page":"313","volume":"19","author":"Marcus Mitchell P.","journal-title":"Computational Linguistics"},{"key":"rf15","author":"Kingsbury Paul","journal-title":"Language Resources and Evaluation"}],"container-title":["International Journal of Semantic Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S1793351X07000238","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T00:43:15Z","timestamp":1565138595000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S1793351X07000238"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,12]]},"references-count":5,"journal-issue":{"issue":"04","published-online":{"date-parts":[[2012,1,25]]},"published-print":{"date-parts":[[2007,12]]}},"alternative-id":["10.1142\/S1793351X07000238"],"URL":"https:\/\/doi.org\/10.1142\/s1793351x07000238","relation":{},"ISSN":["1793-351X","1793-7108"],"issn-type":[{"value":"1793-351X","type":"print"},{"value":"1793-7108","type":"electronic"}],"subject":[],"published":{"date-parts":[[2007,12]]}}}