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The semantic representation of a sentence is a formal structure derived from discourse representation theory and containing distributional vectors. This structure is dynamically and incrementally built by integrating knowledge about events and their typical participants, as they are activated by lexical items. Event knowledge is modelled as a graph extracted from parsed corpora and encoding roles and relationships between participants that are represented as distributional vectors. SDM is grounded on extensive psycholinguistic research showing that generalized knowledge about events stored in semantic memory plays a key role in sentence comprehension.We evaluate SDMon two recently introduced compositionality data sets, and our results show that combining a simple compositionalmodel with event knowledge constantly improves performances, even with dif ferent types of word embeddings.<\/jats:p>","DOI":"10.1017\/s1351324919000214","type":"journal-article","created":{"date-parts":[[2019,7,31]],"date-time":"2019-07-31T11:33:09Z","timestamp":1564572789000},"page":"483-502","source":"Crossref","is-referenced-by-count":12,"title":["A structured distributional model of sentence meaning and processing"],"prefix":"10.1017","volume":"25","author":[{"given":"E.","family":"Chersoni","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"E.","family":"Santus","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"L.","family":"Pannitto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A.","family":"Lenci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P.","family":"Blache","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"C.-R.","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2019,7,31]]},"reference":[{"key":"S1351324919000214_ref74","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-2100"},{"key":"S1351324919000214_ref73","unstructured":"Zaremba W. , Sutskever I. and Vinyals O. 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