demo scraping recent WikiNews

20240519_qa_public.jsonl

@@ -0,0 +1,5 @@
+{"question_date": "2024/05/14", "question_url": "https://en.wikinews.org/wiki/Police_identify_man%27s_body_found_in_a_canal_in_Miami_Gardens,_Florida", "question_sentence": "Where was Christopher Lee Henry's body found?", "links": ["https://www.cbsnews.com/miami/news/police-id-body-of-man-found-shot-multiple-times-bound-along-miami-gardens-canal/", "https://www.msn.com/en-us/news/other/police-id-man-found-shot-to-death-in-miami-gardens-with-hands-tied-and-bag-on-his-head/ar-BB1mkmUi?ocid=BingNewsSearch"], "choices": ["In a park", "Along a canal bank", "In a shopping mall", "In a forest"], "answer_text": "Along a canal bank", "answer": [1], "question_id": "20240519_0", "question_source": "WikiNews"}
+{"question_date": "2024/05/14", "question_url": "https://en.wikinews.org/wiki/Police_identify_man%27s_body_found_in_a_canal_in_Miami_Gardens,_Florida", "question_sentence": "What was notable about the condition in which Christopher Lee Henry was found?", "links": ["https://www.cbsnews.com/miami/news/police-id-body-of-man-found-shot-multiple-times-bound-along-miami-gardens-canal/", "https://www.msn.com/en-us/news/other/police-id-man-found-shot-to-death-in-miami-gardens-with-hands-tied-and-bag-on-his-head/ar-BB1mkmUi?ocid=BingNewsSearch"], "choices": ["He was wearing a suit", "His hands were bound behind his back", "He was unscathed", "He was holding a note"], "answer_text": "His hands were bound behind his back", "answer": [1], "question_id": "20240519_1", "question_source": "WikiNews"}
+{"question_date": "2024/05/14", "question_url": "https://en.wikinews.org/wiki/Police_identify_man%27s_body_found_in_a_canal_in_Miami_Gardens,_Florida", "question_sentence": "What did the police offer for information leading to an arrest?", "links": ["https://www.cbsnews.com/miami/news/police-id-body-of-man-found-shot-multiple-times-bound-along-miami-gardens-canal/", "https://www.msn.com/en-us/news/other/police-id-man-found-shot-to-death-in-miami-gardens-with-hands-tied-and-bag-on-his-head/ar-BB1mkmUi?ocid=BingNewsSearch"], "choices": ["$500", "$1,000", "$5,000", "$10,000"], "answer_text": "$5,000", "answer": [2], "question_id": "20240519_2", "question_source": "WikiNews"}
+{"question_date": "2024/05/14", "question_url": "https://en.wikinews.org/wiki/Police_identify_man%27s_body_found_in_a_canal_in_Miami_Gardens,_Florida", "question_sentence": "How long has Angie Ardavin, the witness, lived in the area?", "links": ["https://www.cbsnews.com/miami/news/police-id-body-of-man-found-shot-multiple-times-bound-along-miami-gardens-canal/", "https://www.msn.com/en-us/news/other/police-id-man-found-shot-to-death-in-miami-gardens-with-hands-tied-and-bag-on-his-head/ar-BB1mkmUi?ocid=BingNewsSearch"], "choices": ["5 years", "10 years", "15 years", "20 years"], "answer_text": "15 years", "answer": [2], "question_id": "20240519_3", "question_source": "WikiNews"}
+{"question_date": "2024/05/14", "question_url": "https://en.wikinews.org/wiki/Police_identify_man%27s_body_found_in_a_canal_in_Miami_Gardens,_Florida", "question_sentence": "What was the method of murder used on Christopher Lee Henry?", "links": ["https://www.cbsnews.com/miami/news/police-id-body-of-man-found-shot-multiple-times-bound-along-miami-gardens-canal/", "https://www.msn.com/en-us/news/other/police-id-man-found-shot-to-death-in-miami-gardens-with-hands-tied-and-bag-on-his-head/ar-BB1mkmUi?ocid=BingNewsSearch"], "choices": ["Stabbing", "Strangulation", "Shooting", "Poisoning"], "answer_text": "Shooting", "answer": [2], "question_id": "20240519_4", "question_source": "WikiNews"}

README.md

@@ -22,6 +22,7 @@ Prerequisites: `pip install openai lxml cssselector requests xmltodict` and Open
 I've added two scripts:
 - scrape.py : base script to load plain text from the latest WikiNews articles
 - scrape_with_openai.py : pass scraped text to OpenAI's GPT-4o to generate questions and answers for each article
+- scrape_morerecent_with_openai.py : scrape recent articles which WikiNews hasn't yet published from `Category:May 2024`, then use OpenAI's GPT-4o for Q&A
 
 An LLM evaluated on this Q&A could read the WikiNews summary, the links collected from the story, or do its own web searches.
 
@@ -48,4 +49,4 @@ year={2023},
 eprint={2207.13332},
 url={https://openreview.net/forum?id=HfKOIPCvsv}
 }
-```
+```

scrape_morerecent_with_openai.py

@@ -0,0 +1,116 @@
+# pip install openai lxml cssselector requests xmltodict
+
+from datetime import date, datetime, timedelta
+import json
+import lxml.html
+from lxml.cssselect import CSSSelector
+import time
+
+from openai import OpenAI
+import requests
+import xmltodict
+
+tabooWords = ['deletion', 'rape', 'rapist', 'abuse', 'minor']
+
+# load from WikiNews English recent days (not yet published)
+recentArticles = []
+dateForArticle = {}
+today = date.today()
+for days in range(5, 12):
+  tdate = (today - timedelta(days=days))
+  tstamp = tdate.strftime("%B_%d,_%Y")
+  r = requests.get(f"https://en.wikinews.org/wiki/Category:{tstamp}")
+  contents = lxml.html.fromstring(r.content)
+  selAnchor = CSSSelector('a')
+  for linkEl in selAnchor(contents):
+    link = str(linkEl.get('href'))
+    if link[:6] == '/wiki/' and '/Special:' not in link and '/Category:' not in link and 'Main_Page' not in link and 'Help:' not in link and 'Wikinews:' not in link and 'File:' not in link:
+      recentArticles.append(link)
+      dateForArticle[link] = tdate.strftime("%Y/%m/%d")
+  time.sleep(1)
+
+client = OpenAI()
+
+outputs = []
+for article in recentArticles:
+  print(article)
+  r = requests.get(f"https://en.wikinews.org{article}")
+  contents = lxml.html.fromstring(r.content)
+
+  selMain = CSSSelector('.mw-body-content p')
+  plaintxt = ""
+  for para in selMain(contents):
+    c = para.text_content()
+    if 'pre-publication review' in c or 'last amended' in c:
+      continue
+    plaintxt += c + "\n"
+  if 'Have an opinion' in plaintxt:
+    plaintxt = plaintxt[:plaintxt.index('Have an opinion')]
+
+  plaintxt = plaintxt.strip()
+
+  block = False
+  for taboo in tabooWords:
+    if taboo in plaintxt.lower():
+      block = True
+  if block:
+    print("Article marked for deletion or about subject sensitive for AI summarization")
+    continue
+
+  dt = dateForArticle[article]
+
+  selAnchor = CSSSelector('a[rel="nofollow"]')
+  foundElements = selAnchor(contents)
+  articleLinks = []
+  for el in foundElements:
+    link = el.get('href')
+
+    linkblocks = ['/wiki/', '.com/intent/tweet', 'creativecommons.org/licenses', 'facebook.com/sharer.php', 'mailto:', 'reddit.com/submit', 'linkedin.com/shareArticle']
+    block = False
+    for blocker in linkblocks:
+      if blocker in link.lower():
+        block = True
+    if block:
+      continue
+
+    articleLinks.append(link)
+
+  qs = []
+  response = client.chat.completions.create(
+    model="gpt-4o",
+    messages=[
+      {
+        "role": "system",
+        "content": "You will be provided with an article from today's news. Provide 3-5 multiple choice questions based on the content of the article, especially newly-introduced facts or knowledge. Don't make the correct answer any more specific, numeric, or realistic compared to the others.\n Respond in JSON format: [{ question: 'Who was elected president of Sesame Street?', choices: ['Big Bird', 'Donald Duck'], answer: 'Big Bird' }]",
+      },
+      {
+        "role": "user",
+        "content": f"Here's the article: \n{plaintxt}",
+      },
+    ],
+  )
+  reply = response.choices[0].message.content
+  reply = reply[reply.index('[') : reply.rindex(']') + 1]
+  qs = json.loads(reply)
+
+  for q in qs:
+    if q["answer"] not in q["choices"]:
+      continue
+
+    outputs.append({
+      "question_date": dt,
+      "question_url": f"https://en.wikinews.org{article}",
+      "question_sentence": q["question"],
+      "links": articleLinks,
+      "choices": q["choices"],
+      "answer_text": q["answer"],
+      "answer": [ q["choices"].index(q["answer"]) ],
+    })
+  time.sleep(1)
+
+tstamp = datetime.now().strftime("%Y%m%d")
+with open(f"./{tstamp}_qa_public.jsonl", "w") as fi:
+  for idx, op in enumerate(outputs):
+    op["question_id"] = f"{tstamp}_{idx}"
+    op["question_source"] = "WikiNews"
+    fi.write(json.dumps(op) + "\n")