Update README.md

README.md

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     path: data/test-*
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+# ghigliottinAI MCQA
+
+Original Papers: https://ghigliottin-ai.github.io/ https://nlp4fun.github.io/
+
+Starting from two different EVALITA tasks, nlp4fun (EVALITA 2018) and ghigliottin-AI (EVALITA 2020), we collected cc. 600 different games extracted from TV show and from BOARDGAME of "L'Eredità".
+
+"La Ghigliottina" is a complex game, to be solved, it needs a very large comprehension of the italian cultural knowledge. It consists in: given five different, uncorrelated words, the solution is a word that is a shared concept between them.
+The original game itself is not well-posed, the solution is not unique, and list all the possible solution is not a affordable. We decided to reframe the problem as a Multi-choice QA, where four possible words are listed and between them all but one are incorrect answers to the game.
+
+## Distractor Generation
+
+For each game the three distractor was chosen among all the possible italian words, the distractor was chosen to be aligned with 3 out of 5 hints and distant to the other ones (computing the cosine similarity in FastTest static embeddings).
+Moreover, the distractors was chosen to have lenght at most len(solution) + 1.
+
+With this setting, we created three different words that are not the possible solution of the game, making a task relativelly simple to be solved by humans, but not that much for Language Models.