Pynsett: A programmable relation extractor
Alberto Cetoli

TL;DR
Pynsett introduces a flexible, rule-based relation extraction approach that uses semantic graphs and plain English rules to extract relations, especially useful for specialized ontologies with limited data.
Contribution
It presents a novel programmable relation extraction method leveraging semantic graphs and user-defined English rules for improved flexibility.
Findings
Effective in extracting specialized ontologies
Requires minimal training data
Flexible rule-based pattern matching
Abstract
This paper proposes a programmable relation extraction method for the English language by parsing texts into semantic graphs. A person can define rules in plain English that act as matching patterns onto the graph representation. These rules are designed to capture the semantic content of the documents, allowing for flexibility and ad-hoc entities. Relation extraction is a complex task that typically requires sizable training corpora. The method proposed here is ideal for extracting specialized ontologies in a limited collection of documents.
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Semantic Web and Ontologies
