{"id":151605,"date":"2002-05-01T00:00:00","date_gmt":"2002-05-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/language-neutral-representation-of-syntactic-structure\/"},"modified":"2018-10-16T21:16:12","modified_gmt":"2018-10-17T04:16:12","slug":"language-neutral-representation-of-syntactic-structure","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/language-neutral-representation-of-syntactic-structure\/","title":{"rendered":"Language-Neutral Representation of Syntactic Structure"},"content":{"rendered":"<div class=\"asset-content\">\n<p>We propose a semantically motivated linguistic representation called Language-Neutral Syntax (LNS), which is scalable in three important respects. First, though information stored in LNS is directly related to the surface tree, it is abstract enough to normalize many surface variations both within and across languages. Second, LNS is adaptable to new applications, in that any application that requires a particular kind of semantic information can extract that information from LNS. Finally, since LNS is developed as part of a broad-coverage parser, it is designed to handle a wide range of constructions. LNS is currently implemented in a large-scale, multi-lingual natural language understanding system, and is used in applications requiring various kinds of semantic information, including question answering and machine translation.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We propose a semantically motivated linguistic representation called Language-Neutral Syntax (LNS), which is scalable in three important respects. First, though information stored in LNS is directly related to the surface tree, it is abstract enough to normalize many surface variations both within and across languages. Second, LNS is adaptable to new applications, in that any [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13545],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-151605","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-language-technologies","msr-locale-en_us"],"msr_publishername":"European Media Laboratory 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