The acquisition of syntactic knowledge
The acquisition of syntactic knowledge
Mechanisms of sentence processing: assigning roles to constituents
Parallel distributed processing
Augmenting and Efficiently Utilizing Domain Theory in Explanation-Based Natural Language Acquisition
ML '92 Proceedings of the Ninth International Workshop on Machine Learning
How to encode semantic knowledge: a method for meaning representation and computer-aided acquisition
Computational Linguistics
From grammar to lexicon: unsupervised learning of lexical syntax
Computational Linguistics - Special issue on using large corpora: II
Lexical semantic techniques for corpus analysis
Computational Linguistics - Special issue on using large corpora: II
Improved portability and parsing through interactive acquisition of semantic information
ANLC '88 Proceedings of the second conference on Applied natural language processing
The acquisition of lexical knowledge from combined machine-readable dictionary sources
ANLC '92 Proceedings of the third conference on Applied natural language processing
Automatic learning for semantic collocation
ANLC '92 Proceedings of the third conference on Applied natural language processing
From N-grams to collocations: an evaluation of Xtract
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
An empirical study on thematic knowledge acquisition based on syntactic clues and heuristics
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Automatic acquisition of the lexical semantics of verbs from sentence frames
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Structural patterns vs. string patterns for extracting semantic information from dictionaries
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Design of a hybrid deterministic parser
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 1
Tagging for learning: collecting thematic relations from corpus
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 1
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Human intervention and/or training corpora tagged with various kinds of information were often assumed in many natural language acquisition models. This assumption is a major source of inconsistencies, errors, an d inefficiency in learning. In this paper, we explore the extent to which a parser may extend it-self without relying on extra input from the outside world. A learning technique called SEP is proposed and attached to the parser. The input to SEP is raw sentences, while the output is the knowledge that is missing in the parser. Since parsers and raw sentences are commonly available and no human intervention is needed in learning, SEP could make fully automatic large-scale acquisition more feasible.