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license: mit |
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# GeoNames Semantic Primes |
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## Dataset Overview |
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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. |
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## Dataset Construction |
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The dataset is constructed by deriving and building the semantic tower - an ensemble of primitive semantic information related to a term - of 660 category classes related to geographical locations. These locations are themselves classified into 9 higher-level categories, e.g. H for stream, lake, and sea, and R for road and railroad and are derived from the original GeoNames dataset. |
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The semantic tower encompasses information gathered from Wikidata, specifically: |
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- label |
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- instance of |
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- subclass of |
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- part of |
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- represents |
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- description |
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This information forms the smallest subset of knowledge needed to distinguish a term from another. |
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## Embeddings Generation |
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The vector embeddings are generated using the [General Text Embeddings (GTE)](https://huggingface.co./thenlper/gte-large) large model. |
