Nested Named Entity Recognition
44 papers with code • 6 benchmarks • 11 datasets
Nested named entity recognition is a subtask of information extraction that seeks to locate and classify nested named entities (i.e., hierarchically structured entities) mentioned in unstructured text (Source: Adapted from Wikipedia).
Benchmarks
These leaderboards are used to track progress in Nested Named Entity Recognition
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Datasets
GENIA
ACE 2005
ACE 2004
NNE
GUM
Chilean Waiting List
The QUAERO French Medical Corpus
Latest papers with no code
RNN Transducers for Nested Named Entity Recognition with constraints on alignment for long sequences
Through empirical experiments on a challenging real-world medical NER task with multiple nested ontologies, we demonstrate that our fixed alignment model outperforms the standard RNN-T model, improving F1-score from 0. 70 to 0. 74.
Simple yet Powerful: An Overlooked Architecture for Nested Named Entity Recognition
The results show that standard NER metrics do not measure well the ability of a model to detect nested entities, while our task-specific metrics provide new evidence on how existing approaches handle the task.
Fusing Heterogeneous Factors with Triaffine Mechanism for Nested Named Entity Recognition
To fuse these heterogeneous factors, we propose a novel triaffine mechanism including triaffine attention and scoring.
Nested Named Entity Recognition as Latent Lexicalized Constituency Parsing
They treat nested entities as partially-observed constituency trees and propose the masked inside algorithm for partial marginalization.
Semantic Parsing in Task-Oriented Dialog with Recursive Insertion-based Encoder
At the generation time, the model constructs the semantic parse tree by recursively inserting the predicted non-terminal labels at the predicted positions until termination.
BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledge
While named entity recognition (NER) is a key task in natural language processing, most approaches only target flat entities, ignoring nested structures which are common in many scenarios.
Effect of depth order on iterative nested named entity recognition models
We provide a set of experiments to study the model's capabilities and the effects of the order on performance.
Named Entity Recognition in the Style of Object Detection
In this work, we propose a two-stage method for named entity recognition (NER), especially for nested NER.
Hierarchical Region Learning for Nested Named Entity Recognition
Named Entity Recognition (NER) is deeply explored and widely used in various tasks.
CopyNext: Explicit Span Copying and Alignment in Sequence to Sequence Models
Copy mechanisms are employed in sequence to sequence models (seq2seq) to generate reproductions of words from the input to the output.
