Amend dataset

AmericanStories.py

@@ -1,9 +1,8 @@
 import json
 import datasets
 
-SUPPORTED_YEARS = ["1774"]
-# Add years from 1798 to 1964 to the supported years
-SUPPORTED_YEARS = SUPPORTED_YEARS + [str(year) for year in range(1798, 1964)]
+SUPPORTED_YEARS = ["1770", "1771", "1772", "1773", "1774", "1777", "1778, "1779", 
+                   "1791", "1792", "1793"] + [str(year) for year in range(1796, 1964+1)]
 
 def make_year_file_splits():
     """
@@ -16,7 +15,6 @@ def make_year_file_splits():
 
     base_url = "https://huggingface.co/datasets/dell-research-harvard/AmericanStories/resolve/main/"
 
-    # Make a list of years from 1774 to 1960
     # TODO: can we set up to check the actual files in the repo instead of relying on the offline list?
     year_list = SUPPORTED_YEARS
     data_files = [f"faro_{year}.tar.gz" for year in year_list]
@@ -29,7 +27,7 @@ def make_year_file_splits():
 
 
 _CITATION = """\
-Coming Soon
+@misc{dell2023american, title={American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers}, author={Melissa Dell and Jacob Carlson and Tom Bryan and Emily Silcock and Abhishek Arora and Zejiang Shen and Luca D'Amico-Wong and Quan Le and Pablo Querubin and Leander Heldring}, year={2023}, eprint={2308.12477}, archivePrefix={arXiv}, primaryClass={cs.CL} }
 """
 
 _DESCRIPTION = """\
@@ -56,7 +54,7 @@ class CustomBuilderConfig(datasets.BuilderConfig):
 class AmericanStories(datasets.GeneratorBasedBuilder):
     """Dataset builder class for AmericanStories dataset."""
 
-    VERSION = datasets.Version("0.1.0")
+    VERSION = datasets.Version("0.2.0")
 
     BUILDER_CONFIGS = [
         CustomBuilderConfig(
@@ -153,7 +151,7 @@ class AmericanStories(datasets.GeneratorBasedBuilder):
                 name=year,
                 gen_kwargs={
                     "files": dl_manager.iter_archive(archive[year]),
-                    "year_dir": "/".join(["mnt", "122a7683-fa4b-45dd-9f13-b18cc4f4a187", "ca_rule_based_fa_clean", "faro_" + year]),
+                    "year_dir": "/".join(["faro_" + year]),
                     "split": year,
                     "associated": True if not self.config.name.endswith("content_regions") else False,
                 },

README.md

@@ -38,6 +38,8 @@ size_categories:
   Additionally, the structured article texts in the dataset enable the use of transformer-based methods for applications such as detecting reproduced content. This significantly enhances accuracy compared to relying solely on existing OCR techniques.
   The American Stories dataset serves as an invaluable resource for developing multimodal layout analysis models and other multimodal applications. Its vast size and silver quality make it ideal for innovation and research in this domain.
 
+  *Update (3/25/2025)* We have updated this dataset to include instances that were missing from the earlier version. For reproducibility, a checkpoint of the earlier version has been preserved and can be accessed by specifying `revision="v0.1.0"` when loading the dataset using the Hugging Face Datasets library.
+  
 ### Languages
 
 English (en)

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