A Novel Approach to a Semantically-Aware Representation of Items (NASARI)
Semantic Textual SimilarityMulti-Lingual
A Novel Approach to a Semantically-Aware Representation of Items (NASARI) is a semantic textual similarity-focused dataset in Multi-Lingual that provides 610K-4.4M depending on language labeled examples distributed in Text format.
About A Novel Approach to a Semantically-Aware Representation of Items (NASARI)
Dataset contains semantic vector representations for BabelNet synsets and Wikipedia pages in several languages: English, Spanish, French, German and Italian. Currently available three vector types: lexical, unified and embedded.
Details
- Task
- Semantic Textual Similarity
- Language
- Multi-Lingual
- Format
- Text
- Rows / instances
- 610K-4.4M depending on language
- Creator
- Camacho-Collados et al.
- Year
- 2016