Chunking
67 papers with code • 5 benchmarks • 5 datasets
Chunking, also known as shallow parsing, identifies continuous spans of tokens that form syntactic units such as noun phrases or verb phrases.
Example:
| Vinken | , | 61 | years | old |
|---|---|---|---|---|
| B-NLP | I-NP | I-NP | I-NP | I-NP |
Benchmarks
These leaderboards are used to track progress in Chunking
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Libraries
Use these libraries to find Chunking models and implementations
Penn Treebank
CoNLL 2003
Most implemented papers
Boundary-based MWE segmentation with text partitioning
This work presents a fine-grained, text-chunking algorithm designed for the task of multiword expressions (MWEs) segmentation.
Keystroke dynamics as signal for shallow syntactic parsing
Keystroke dynamics have been extensively used in psycholinguistic and writing research to gain insights into cognitive processing.
Neural Models for Sequence Chunking
threelittlemonkeys/pointer-network-pytorch
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Many natural language understanding (NLU) tasks, such as shallow parsing (i. e., text chunking) and semantic slot filling, require the assignment of representative labels to the meaningful chunks in a sentence.
NNVLP: A Neural Network-Based Vietnamese Language Processing Toolkit
This paper demonstrates neural network-based toolkit namely NNVLP for essential Vietnamese language processing tasks including part-of-speech (POS) tagging, chunking, named entity recognition (NER).
Review highlights: opinion mining on reviews: a hybrid model for rule selection in aspect extraction
We introduce a hybrid technique which combines machine learning and rule based model.
Robust Multilingual Part-of-Speech Tagging via Adversarial Training
Adversarial training (AT) is a powerful regularization method for neural networks, aiming to achieve robustness to input perturbations.
Does Higher Order LSTM Have Better Accuracy for Segmenting and Labeling Sequence Data?
lancopku/Multi-Order-LSTM
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COLING 2018
In our work, we first design a new model called "high order LSTM" to predict multiple tags for the current token which contains not only the current tag but also the previous several tags.
A Feature-Rich Vietnamese Named-Entity Recognition Model
We also explore the effects of word segmentation, PoS tagging, and chunking results of many popular Vietnamese NLP toolkits on the accuracy of the proposed feature-based NER model.
A Tree Search Algorithm for Sequence Labeling
YadiLao/MM-Tag
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Inspired by the success and methodology of the AlphaGo Zero, MM-Tag formalizes the problem of sequence tagging with a Monte Carlo tree search (MCTS) enhanced Markov decision process (MDP) model, in which the time steps correspond to the positions of words in a sentence from left to right, and each action corresponds to assign a tag to a word.
