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Projects
FrameNet Project
The FrameNet project, developed since 1997 at ICSI and now affiliated with the UC Berkeley Linguistics Department, helps machines—and people—understand language by curating more than 1,000 semantic frames and annotating expert annotators.
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A database to teach computers meaning
If we want computers to be able to understand language the way we do, we need to teach them to understand semantic frames, which describe a type of event, relation, or entity and the participants in it. FrameNet, which was developed at ICSI and is now hosted by UC Berkeley, is a lexical database that defines more than 13,000 lexical units (word senses) in over 1,000 semantic frames.
The system draws from over 200,000 manual annotations documenting how words are used in actual texts and is designed to be readable by both machines and people. FrameNet’s rich trove of data, freely available for download, has proved valuable for research in machine learning, information extraction, and reasoning about events, as well as for deepening human understanding of vocabulary and grammar.
Project Team
Outcomes
About
Sponsors
- National Science Foundation
- Defense Threat Reduction Agency
Focus Areas
- Knowledge Representation and Automated Reasoning
- AI in Healthcare, Biomedicine, and Life Sciences
- AI for Humanitarian Aid, Disaster Response, and Social Good
- Machine Translation and Multilingual Language Models
- Information Retrieval, Search Engines, and Question Answering
- Text Analytics: Sentiment Analysis, Summarization, Topic Modeling
- Conversational AI, Dialogue Systems, and Chatbots
- Low-Resource, Cross-Lingual, and Inclusive NLP
- Databases, Data Management, and Storage Systems
- Multimodal Perception (Vision + Language + Audio)
Get in touch
Want to discuss opportunities to work with ICSI? We’d love to hear from you.