Update README.md

README.md

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-Factuality Evaluation of LLMs.
+WildHallucinations is designed for evaluating the factuality of LLMs. 
+Its core idea is to prompt LLMs to generate and fact-check information about a diverse set of entities.
+WildHallucinations consists of 7917 entities extracted from WildChat and a knowledge source.
+These entities come from English conversations that are marked as non-toxic.
+As described in the main paper, we apply extensive filtering for quality control,
+especially for removing entities with more than one meaning.
+The knowledge source is constructed from Google search API. We scrape the top 10 web pages for each entity.
+Additional cleaning process can be found in the paper.
+
+To use the dataset:
+```
+from datasets import load_dataset
+ds = load_dataset("wentingzhao/WildHallucinations", split="train")
+```
+
+Dataset Columns:
+ * entity (string): the entity name
+ * perplexity (float): the perplexity of the entity measured by the Llama-3-8B model
+ * info (string): the web information about the entity scraped from Google search results
+ * category (string): the category of the entity annotated by either an author or GPT-4o
+ * wiki (Boolean): whether any information about the entity comes from wikipedia.org