lil-lab/spf

Cornell Semantic Parsing Framework

39
/ 100
Emerging

This framework helps computer science researchers and natural language processing practitioners translate human language into a formal, machine-understandable representation. It takes text-based instructions or questions as input and outputs structured logical forms, allowing machines to interpret and act on commands. Researchers focusing on natural language understanding would find this valuable.

131 stars. No commits in the last 6 months.

Use this if you are a researcher or advanced practitioner developing systems that need to semantically parse natural language sentences into logical forms for tasks like executing commands or querying structured databases.

Not ideal if you are looking for an off-the-shelf application to solve a specific NLP problem without delving into the underlying semantic parsing mechanisms.

natural-language-processing computational-linguistics semantic-parsing knowledge-representation AI-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 13 / 25

How are scores calculated?

Stars

131

Forks

13

Language

Java

License

GPL-2.0

Last pushed

Mar 07, 2020

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/lil-lab/spf"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.