named-entity-recognition
791 papers with code • 2 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in named-entity-recognition
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Libraries
Use these libraries to find named-entity-recognition models and implementations
NuNER
Latest papers
Fine-Grained Named Entities for Corona News
Information resources such as newspapers have produced unstructured text data in various languages related to the corona outbreak since December 2019.
Intent Detection and Entity Extraction from BioMedical Literature
Biomedical queries have become increasingly prevalent in web searches, reflecting the growing interest in accessing biomedical literature.
BanglaAutoKG: Automatic Bangla Knowledge Graph Construction with Semantic Neural Graph Filtering
Knowledge Graphs (KGs) have proven essential in information processing and reasoning applications because they link related entities and give context-rich information, supporting efficient information retrieval and knowledge discovery; presenting information flow in a very effective manner.
MetaIE: Distilling a Meta Model from LLM for All Kinds of Information Extraction Tasks
We construct the distillation dataset via sampling sentences from language model pre-training datasets (e. g., OpenWebText in our implementation) and prompting an LLM to identify the typed spans of "important information".
Cross-Lingual Transfer Robustness to Lower-Resource Languages on Adversarial Datasets
csu-signal/xlingual-robustness
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Multilingual Language Models (MLLMs) exhibit robust cross-lingual transfer capabilities, or the ability to leverage information acquired in a source language and apply it to a target language.
ELLEN: Extremely Lightly Supervised Learning For Efficient Named Entity Recognition
In a zero-shot setting, ELLEN also achieves over 75% of the performance of a strong, fully supervised model trained on gold data.
Few-shot Named Entity Recognition via Superposition Concept Discrimination
Then a superposition instance retriever is applied to retrieve corresponding instances of these superposition concepts from large-scale text corpus.
Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Data
Named Entity Recognition (NER) is a fundamental task to extract key information from texts, but annotated resources are scarce for dialects.
Evaluating Named Entity Recognition: Comparative Analysis of Mono- and Multilingual Transformer Models on Brazilian Corporate Earnings Call Transcriptions
By curating a comprehensive dataset comprising 384 transcriptions and leveraging weak supervision techniques for annotation, we evaluate the performance of monolingual models trained on Portuguese (BERTimbau and PTT5) and multilingual models (mBERT and mT5).
ProgGen: Generating Named Entity Recognition Datasets Step-by-step with Self-Reflexive Large Language Models
Although Large Language Models (LLMs) exhibit remarkable adaptability across domains, these models often fall short in structured knowledge extraction tasks such as named entity recognition (NER).
