The NLTK FrameNet API: Designing for Discoverability with a Rich Linguistic Resource
Nathan Schneider, Chuck Wooters
TL;DR
The paper introduces a Python API within NLTK that provides easy access to the FrameNet 1.7 lexical database, enabling both programmatic processing and human-readable browsing of linguistic data.
Contribution
It presents a new API design that enhances discoverability and usability of FrameNet data within the NLTK toolkit.
Findings
API allows programmatic access to FrameNet 1.7
Supports browsing with human-readable displays
Facilitates linguistic research and development
Abstract
A new Python API, integrated within the NLTK suite, offers access to the FrameNet 1.7 lexical database. The lexicon (structured in terms of frames) as well as annotated sentences can be processed programatically, or browsed with human-readable displays via the interactive Python prompt.
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Text Readability and Simplification