ABL: An Unsupervised Learning Algorithm for Structured Language

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Title: ABL: An Unsupervised Learning Algorithm for Structured Language

Abstract: This research article introduces ABL (Adaptive Bracket Learning), an unsupervised learning algorithm designed to assign structure to natural language sentences. The algorithm consists of two phases: alignment learning and bracket selection. ABL is capable of generating recursive structures and handling PP attachment, demonstrating its potential for unsupervised language learning. The article presents results of ABL applied to the ATIS and OVIS corpora, showcasing its effectiveness in generating structured sentences. Future research on ABL aims to improve its performance and expand its applications.

Main Research Question: Can an unsupervised learning algorithm effectively assign structure to natural language sentences?

Methodology: The ABL algorithm is composed of two phases: alignment learning and bracket selection. In the alignment learning phase, sentences are paired based on shared words, and possible constituents are identified. The bracket selection phase selects the best constituents from the aligned sentences.

Results: ABL was applied to the ATIS and OVIS corpora, achieving high non-crossing bracket precisions of 86.04% and 89.39%, respectively.

Implications: The ABL algorithm's ability to generate recursive structures and handle PP attachment indicate its potential for unsupervised language learning. Its high performance on the ATIS and OVIS corpora suggest that ABL could be a valuable tool for assigning structure to natural language sentences.

Future Work: Future research on ABL will focus on improving its performance and expanding its applications. This includes exploring different ways to identify possible constituents and developing more efficient bracket selection algorithms. Additionally, research will be conducted to better understand the algorithm's behavior and its limitations.

Link to Article: https://arxiv.org/abs/0104005v1 Authors: arXiv ID: 0104005v1