Bridging the Gap Between Models and Reality: Coreference Effects in Natural Language
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Beschreibung
Natural language processing (NLP) strives to bridge the gap between the complex world of human language and the structured world of machines. Coreference, the phenomenon where words or phrases refer back to previously mentioned entities, plays a crucial role in this endeavor. Understanding and resolving coreference is essential for tasks like machine translation, question answering, and sentiment analysis, as it allows machines to grasp the relationships between elements in a sentence and build a coherent understanding of the text.
The Challenge of Coreference
Human brains excel at coreference resolution. We effortlessly infer who "he," "she," or "it" refers to based on context and world knowledge. However, for machines, coreference presents a significant challenge. Consider the sentence: "The scientist discovered a new element. She named it after her hometown.
Struggling to bridge the gap between theoretical language models and real-world applications? This book explores coreference effects, a critical aspect of natural language understanding, providing valuable insights for researchers and developers working on NLP tasks.
Autor*in
Herlie
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Themen in »Bridging the Gap Between Models and Reality: Coreference Effects in Natural Language«
pragmatics machine learning coreference resolution semantics anaphora ellipsis bridging inference discourse analysis artificial intelligence text comprehension language models