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tweet contextualization task: the idea is to expand a collection of n initial (ambiguous) tweets (S_{t_{ in}})=({t_{{ in}_{1}},ldots,t_{{ initial}_{n}})} using a collection of m Twitter conversations (S_{ c}={c_{1},ldots,c_{m}}) by providing a context (C_{i}) for each tweet (t_{{ in}_{i}} in S_{t_{ in}}).
Formally, we have (t_{{ in}_{i}}={h_{1},ldots,h_{j}}) tweet contextualization task: the idea is to expand a collection of n initial (ambiguous) tweets (S_{t_{ in}})=({t_{{ in}_{1}},ldots,t_{{ initial}_{n}})} using a collection of m Twitter conversations (S_{ c}={c_{1},ldots,c_{m}}) by providing a context (C_{i}) for each tweet (t_{{ in}_{i}} in S_{t_{ in}}).
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Students must therefore work without any wish to gain good marks, to pass examinations, to win school successes; without any reference to their natural abilities and tastes; applying themselves equally to all their tasks, with the idea that each one will help form in them the habit of that attention which is the substance of prayer..
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com