task_categories:question-answering size_categories:100K<n<1M language:en license:mit region:us
---

license: mit
task_categories:
- question-answering
language:
- en
size_categories:
- 100K<n<1M
annotations_creators:
- {creator}  # Example: found
source_datasets:
- {source_dataset_0}  # All names data products are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names.

---
<p align="center"><h1> Domestic Names from the Federal Government's repository of official geographic names [CSV dataset]</h1></p>

This Dataset includes 980,065 geographic names as of September 10, 2023.

It is apparent that no currently released LLMs are pretrained on datasets with many of these geographic names (i.e., features), descriptions, and histories. 

Example: *feature_name: Abercrombie Gulch* 
- GPT-3.5 responds "I'm not aware of a specific location called Abercrombie Gulch in my training data,..." when prompted about this name.
- Here is the description found in this Dataset about that name. "Abercrombie Gulch trends N-S 3 mi. on a tributary of Lowe River, 2.5 mi. S of Valdez; Chugach Mts. Named in 1911 by J. W. Bagley, and F. E. Giffin, U.S. Geological Survey (USGS), for Captain William R. Abercrombie, USA, who explored this area in 1884 and 1898-99."

This Dataset also includes geographic point locations.

All domestic names are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names. This Dataset is deduped, zero values are changed to null, and the sort order is randomized. This Dataset combines 56 domestic names files from [here](https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/GeographicNames/DomesticNames/) and then merged with description and history for historical features when found in **HistoricalFeatures_National_Text** [here](https://prd-tnm.s3.amazonaws.com/index.html?prefix=StagedProducts/GeographicNames/Topical/).
