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hot spring(s) | spring,inns,located in the administrative territorial entity,public bath in japan,facilities,street address,has facility,temperature,fee,japanese hot spring and its associated bathing facilities and inns,phone number,country,bathing,hot springs of japan,spa,open days,mineral spring | [-0.02322094887495041, 0.023217901587486267, -0.009182911366224289, -0.04145162180066109, 0.0020542226266115904, 0.004722085781395435, 0.021673718467354774, 0.011880998499691486, 0.01591193489730358, 0.05214427039027214, 0.04165225476026535, 0.033831752836704254, 0.021780306473374367, -0.05581759288907051, -0.019138101488351822, -0.036950353533029556, -0.028067348524928093, -0.023749884217977524, 0.0004794108681380749, -0.0010765156475827098, 0.007842503488063812, 0.030846888199448586, -0.05158400908112526, 0.006367143243551254, -0.030569443479180336, 0.02255467139184475, 0.034796092659235, 0.010647722519934177, 0.03870164230465889, 0.049800485372543335, -0.02144409529864788, 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intermittent lakes | karst area,seasonal lakes of pivka,group of interconnected lakes | "[-0.03582056611776352, 0.010864040814340115, -0.009265778586268425, -0.004841347690671682, -0.03267(...TRUNCATED) |
maneuver area | "tract,exercises,human-geographic territorial entity,tract of land where military field exercises ar(...TRUNCATED) | "[-0.01975652389228344, 0.016831019893288612, -0.007792313117533922, 0.01260372344404459, -0.0230557(...TRUNCATED) |
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GeoNames 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 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.
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.
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