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NER

The named entity recognition (NER) involves identification of key information in the text and classification into a set of predefined categories. This includes standard entities in the text like Part of Speech (PoS) and entities like places, names etc...

Papers

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Showing 71–80 of 1729 papers

TitleStatusHype
Joint Automatic Speech Recognition And Structure Learning For Better Speech UnderstandingCode0
Building Foundations for Natural Language Processing of Historical Turkish: Resources and Models—0
Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case StudyCode0
BabyLMs for isiXhosa: Data-Efficient Language Modelling in a Low-Resource Context—0
Prune or Retrain: Optimizing the Vocabulary of Multilingual Models for Estonian—0
Financial Named Entity Recognition: How Far Can LLM Go?Code0
GliLem: Leveraging GliNER for Contextualized Lemmatization in Estonian—0
Text2Insight: Transform natural language text into insights seamlessly using multi-model architecture—0
"I've Heard of You!": Generate Spoken Named Entity Recognition Data for Unseen EntitiesCode0
Semi-Supervised Learning from Small Annotated Data and Large Unlabeled Data for Fine-grained PICO Entity Recognition—0
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