metadata

license: mit

WordNet Semantic Primes

Dataset Overview

We propose a dataset at the core of our semantic towers methodology which combines vectorized knowledge graph information to augment a Retrieval-and-Generation (RAG) pipeline.

Dataset Construction

The dataset is constructed by deriving and building the semantic tower - an ensemble of primitive semantic information related to a term - of 4 term types (noun, verb, adverb, adjective). These term typed are derived from a data dump from the original WordNet dataset.

The semantic tower encompasses information gathered from Wikidata, specifically:

label
instance of
subclass of
part of
represents
description

This information forms the smallest subset of knowledge needed to distinguish a term from another.

Embeddings Generation

The vector embeddings are generated using the General Text Embeddings (GTE) large model.