{"type":"ScholarlyArticle","title":"Partial-Tree Linearization: Generalized Word Ordering for Text Synthesis","authors":[{"name":"Yue Zhang","slug":"yue-zhang","given":"Yue","family":"Zhang","affiliation":""}],"abstract":"We present partial-tree linearization, a generalized word ordering (i.e. ordering a set of input words into a grammatical and fluent sentence) task for text-to-text applications. Recent studies of word ordering can be categorized into either abstract word ordering (no input syntax except for POS) or tree linearization (input words are associated with a full unordered syntax tree). Partial-tree linearization covers the whole spectrum of input between these two extremes. By allowing POS and dependency relations to be associated with any subset of input words, partial-tree linearization is more practical for a dependency-based NLG pipeline, such as transfer-based MT and abstractive text summarization. In addition, a partial-tree linearizer can also perform abstract word ordering and full-tree linearization. Our system achieves the best published results on standard PTB evaluations of these tasks.","doi":null,"url":"https://ijcai.org/proceedings/2013/329","pdf":"https://ijcai.org/proceedings/2013/0329.pdf","markdown":"https://ijcai.org/proceedings/2013/329.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/329","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":329,"pages":{"first":2232,"last":2237},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}