{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/whats-going-on-in-neural-constituency-parsers","title":"What's Going On in Neural Constituency Parsers? An Analysis","arxiv_id":"1804.07853","date":"2018-04-20","proceeding":"NAACL 2018 6","authors":["David Gaddy","Mitchell Stern","Dan Klein"],"abstract":"A number of differences have emerged between modern and classic approaches to\nconstituency parsing in recent years, with structural components like grammars\nand feature-rich lexicons becoming less central while recurrent neural network\nrepresentations rise in popularity. The goal of this work is to analyze the\nextent to which information provided directly by the model structure in\nclassical systems is still being captured by neural methods. To this end, we\npropose a high-performance neural model (92.08 F1 on PTB) that is\nrepresentative of recent work and perform a series of investigative\nexperiments. We find that our model implicitly learns to encode much of the\nsame information that was explicitly provided by grammars and lexicons in the\npast, indicating that this scaffolding can largely be subsumed by powerful\ngeneral-purpose neural machinery.","url_abs":"http://arxiv.org/abs/1804.07853v1","url_pdf":"http://arxiv.org/pdf/1804.07853v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"whats-going-on-in-neural-constituency-parsers","repo_url":"https://github.com/dgaddy/parser-analysis","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"constituency-parsing","task_name":"Constituency Parsing"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1804.07853","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1804.07853"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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