In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics: Findings. Towards Knowledge-Grounded Counter Narrative Generation for Hate Speech. Yi-Ling Chung, Serra Sinem Tekiroğlu, and Marco Guerini. In the files, each entry has four fields: hate speech, knowledge sentences, counter narrative, and target. Under the folder multitarget_KN_grounded_CN we provide the data in json and csv format. The counter narratives are written by an expert who is tasked with composing a suitable CN response to a given hate speech using the corresponding knowledge as much as possible. The dataset consists of 195 HS-CN pairs covering multiple hate targets (islamophobia, misogyny, antisemitism, racism, and homophobia), provided along with the relevant knowledge automatically retrieved. This small dataset contains hate speech/counter-narrative pairs coupled with the backgroud knowledge used to construct the counter-narrative. Title = " Knowledge-grounded hate countering dataset
Add multiple counters for counting people, knitting, scores, or what ever you want.
#Online multi counter Pc
3+ Free See system requirements Available on PC Description With this app you can count about anything. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Long chung-etal-2019-conan, Add multiple counters for counting people, knitting, scores, or what ever you want.
CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech. Yi-Ling Chung, Elizaveta Kuzmenko, Serra Sinem Tekiroğlu, and Marco Guerini. You can find further details in our paper: Use this online scoreboard with a projector or with a shared big screen to. Pick a font style, and add a timer above the screen. Toggle a secondary clicker and use it as a simple scoreboard. Switch between count up or down and add any number (even negative) as step. (P1: paraphrase 1 / P2: paraphrase 2 / T1: translation 1) Citation Select a theme or set the color scheme manually. Language | HS Type | HS SubTopic | HS ID | CN Count | augmentation type (P1/P2/T1) ID indicates language, hate speech type, hate speech sub-topic, unique hate speech count, counter-narrative count, and augmentation type (if any). In the files each entry starts with an ID, followed by a pair of hate speech/counter-narrative and the metadata (hate speech type, hate speech sub-topic, counter-narrative type, and demographics). Under the folder CONAN we provide the dataset in json and csv format. (*)The original number was 15.024 but after post-hoc analysis, we deleted 9 original pairs (36 pairs including augmented ones) because they did not meet the required standard. The dataset is augmented through translation (from Italian/French to English) and paraphrasing, which brought the total number of pairs to 14.988. Together with the data we also provide 3 types of metadata: expert demographics, hate speech sub-topic and counter-narrative type. The dataset consists of 4,078 pairs over the 3 languages.
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