CogComp/TCR

Temporal and Causal Reasoning (dataset)

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Experimental

This dataset helps researchers and students working in natural language processing (NLP) to analyze how events in text are connected by time and cause-and-effect. It provides annotated text documents as input, and the output helps train or evaluate systems that understand the temporal order and causal links between different actions or happenings described in those texts. It is primarily used by computational linguists, NLP researchers, and AI developers focused on semantic understanding.

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Use this if you are developing or evaluating AI models that need to identify and reason about the 'when' and 'why' of events described within various documents.

Not ideal if you need a tool for direct application or are looking for a dataset beyond English news articles to understand temporal and causal relationships.

natural-language-processing computational-linguistics causal-inference-text event-ordering AI-model-training
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Apr 19, 2022

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