Nominal Phrase

Nominal phrases, fundamental units of language consisting of a noun and its modifiers, are a subject of ongoing research in natural language processing (NLP). Current investigations focus on improving the accuracy of identifying and analyzing nominal phrases, particularly addressing challenges like nominal adjectives and proper noun compounds, often employing machine learning techniques such as Hidden Markov Models, Maximum Entropy models, BERT, and various neural network architectures for word embedding and coreference resolution. This research is crucial for enhancing the performance of NLP tasks such as syntactic parsing, semantic interpretation, and information retrieval, ultimately leading to more robust and accurate language technologies.