Chunking
68 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
Latest papers
Weighted Training for Cross-Task Learning
In this paper, we introduce Target-Aware Weighted Training (TAWT), a weighted training algorithm for cross-task learning based on minimizing a representation-based task distance between the source and target tasks.
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
modelscope/adaseq
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ACL 2021
We find empirically that the contextual representations computed on the retrieval-based input view, constructed through the concatenation of a sentence and its external contexts, can achieve significantly improved performance compared to the original input view based only on the sentence.
Neural Sequence Segmentation as Determining the Leftmost Segments
LeePleased/LeftmostSeg
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NAACL 2021
Prior methods to text segmentation are mostly at token level.
Does Chinese BERT Encode Word Structure?
ylwangy/BERT_zh_Analysis
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COLING 2020
Contextualized representations give significantly improved results for a wide range of NLP tasks.
Automated Concatenation of Embeddings for Structured Prediction
Pretrained contextualized embeddings are powerful word representations for structured prediction tasks.
AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network
Alibaba-NLP/AIN
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EMNLP 2020
The linear-chain Conditional Random Field (CRF) model is one of the most widely-used neural sequence labeling approaches.
Continual General Chunking Problem and SyncMap
zweifel/SyncMap
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Here, we propose a continual generalization of the chunking problem (an unsupervised problem), encompassing fixed and probabilistic chunks, discovery of temporal and causal structures and their continual variations.
Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension
HongyuGong/RCM-Question-Answering
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ACL 2020
In this paper, we study machine reading comprehension (MRC) on long texts, where a model takes as inputs a lengthy document and a question and then extracts a text span from the document as an answer.
The Structured Weighted Violations MIRA
We present the Structured Weighted Violation MIRA (SWVM), a new structured prediction algorithm that is based on an hybridization between MIRA (Crammer and Singer, 2003) and the structured weighted violations perceptron (SWVP) (Dror and Reichart, 2016).
Capturing Global Informativeness in Open Domain Keyphrase Extraction
thunlp/BERT-KPE
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Open-domain KeyPhrase Extraction (KPE) aims to extract keyphrases from documents without domain or quality restrictions, e. g., web pages with variant domains and qualities.
