Datasets:

dell-research-harvard
/

AmericanStories

Tasks:

Text Classification

Text Generation

Languages:

Size:

ArXiv:

Tags:

large language modeling

DOI:

License:

Dataset card Files Files and versions

96abhishekarora commited on Jun 13, 2023

Commit

ef966b2

·

1 Parent(s): 2fd7cf9

test

Files changed (1) hide show

AmericanStories.py +18 -17

AmericanStories.py CHANGED Viewed

@@ -175,20 +175,21 @@ class AmericanStories(datasets.GeneratorBasedBuilder):
         for filepath in os.listdir(year_dir):
             with open(os.path.join(year_dir,filepath), encoding="utf-8") as f:
                     data = json.load(f)
-                    scan_id=filepath.split('.')[0]
-                    scan_date=filepath.split("_")[0]
-                    scan_page=filepath.split("_")[1]
-                    scan_edition=filepath.split("_")[-2][8:]
-                    newspaper_name=data["lccn"]["title"]
-                    full_articles_in_data=data["full articles"]
-                    for article in full_articles_in_data:
-                        article_id=str(article["full_article_id"]) +"_" +scan_id
-                        yield article_id,  {
-                            "newspaper_name": newspaper_name,
-                            "edition": scan_edition,
-                            "date": scan_date,
-                            "page": scan_page,
-                            "headline": article["headline"],
-                            "byline": article["byline"],
-                            "article": article["article"]
-                            }

         for filepath in os.listdir(year_dir):
             with open(os.path.join(year_dir,filepath), encoding="utf-8") as f:
                     data = json.load(f)
+                    if "lccn" in data.keys():
+                        scan_id=filepath.split('.')[0]
+                        scan_date=filepath.split("_")[0]
+                        scan_page=filepath.split("_")[1]
+                        scan_edition=filepath.split("_")[-2][8:]
+                        newspaper_name=data["lccn"]["title"]
+                        full_articles_in_data=data["full articles"]
+                        for article in full_articles_in_data:
+                            article_id=str(article["full_article_id"]) +"_" +scan_id
+                            yield article_id,  {
+                                "newspaper_name": newspaper_name,
+                                "edition": scan_edition,
+                                "date": scan_date,
+                                "page": scan_page,
+                                "headline": article["headline"],
+                                "byline": article["byline"],
+                                "article": article["article"]
+                                }