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1
What is Your Article Based On? Inferring Fine-grained Provenance ...
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2
{Z}ero-shot {L}abel-Aware {E}vent {T}rigger and {A}rgument {C}lassification ...
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Event-Centric Natural Language Processing ...
Abstract: This tutorial targets researchers and practitioners who are interested in AI technologies that help machines understand natural language text, particularly real-world events described in the text. These include methods to extract the internal structures of an event regarding its protagonist(s), participant(s) and properties, as well as external structures concerning memberships, temporal and causal relations of multiple events. This tutorial will provide audience with a systematic introduction of (i) knowledge representations and acquisition of events, (ii) various methods for automated extraction, conceptualization, coreference resolution and prediction of events and their relations, (iii) induction of event processes and properties, and (iv) a wide range of NLP and commonsense understanding tasks that benefit from aforementioned techniques. We will conclude the tutorial by outlining emerging research problems in this area. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://dx.doi.org/10.48448/6rwj-qq95
https://underline.io/lecture/30091-event-centric-natural-language-processing
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4
Zero-shot Event Extraction via Transfer Learning: Challenges and Insights ...
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5
Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary ...
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6
Constrained Labeled Data Generation for Low-Resource Named Entity Recognition ...
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