Temporal Relation Extraction
13 papers with code • 0 benchmarks • 2 datasets
Temporal relation extraction systems aim to identify and classify the temporal relation between a pair of entities provided in a text. For instance, in the sentence "Bob sent a message to Alice while she was leaving her birthday party." one can infer that the actions "sent" and "leaving" entails a temporal relation that can be described as "simultaneous".
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A principal barrier to training temporal relation extraction models in new domains is the lack of varied, high quality examples and the challenge of collecting more.
Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference
There has been a steady need in the medical community to precisely extract the temporal relations between clinical events.
The effects of the interaction between the temporal and the causal components, although limited, yield promising results and confirm the tight connection between the temporal and the causal dimension of texts.
We propose a scalable structured learning model that jointly predicts temporal relations between events and temporal expressions (TLINKS), and the relation between these events and the document creation time (DCTR).
In this work, we extend our classification model's task loss with an unsupervised auxiliary loss on the word-embedding level of the model.
Extracting event temporal relations is a critical task for information extraction and plays an important role in natural language understanding.
We present EventPlus, a temporal event understanding pipeline that integrates various state-of-the-art event understanding components including event trigger and type detection, event argument detection, event duration and temporal relation extraction.