This paper describes a hybrid (symbolic/connectionist) system that performs PP-attachment disambiguation by taking advantage of three distinguishing features of neutral networks: distributed representation, functional compositionality, and inductive learning. The connectionist part of the system follows all the steps performed by the symbolic parser, and drives the parser's behavior by inducing a bias towards the most semantically plausible attachment choices. The sentence to be parsed is read one word at a time. When the symbolic parser has more than one production to apply, the connectionist module has already developed an inner representation of the sentence and a distribution of probabilities over the possible choices. The parser continues its work according to such a distribution.
Free access
An integrated symbolic/connectionist architecture for parsing italian sentences containing pp-attachment ambiguities
Reprints and Corporate Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
To request a reprint or corporate permissions for this article, please click on the relevant link below:
Academic Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
Obtain permissions instantly via Rightslink by clicking on the button below:
If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.