SOTAVerified

Chunking

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 |

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 447 papers

TitleStatusHype
Experiential Explanations for Reinforcement LearningCode0
Repairing Bugs in Python Assignments Using Large Language Models—0
DadmaTools: Natural Language Processing Toolkit for Persian LanguageCode2
BIT-Xiaomi’s System for AutoSimTrans 2022—0
An Experimental Investigation of Part-Of-Speech Taggers for Vietnamese—0
ChordMixer: A Scalable Neural Attention Model for Sequences with Different LengthsCode1
Fine-Grained Error Analysis and Fair Evaluation of Labeled SpansCode0
Query-Based Keyphrase Extraction from Long DocumentsCode0
Introduction to Soar—0
Sketching a Linguistically-Driven Reasoning Dialog Model for Social Talk—0
Shallow Parsing for Nepal Bhasa Complement Clauses—0
The HW-TSC’s Simultaneous Speech Translation System for IWSLT 2022 Evaluation—0
Building Odia Shallow ParserCode0
CUSIDE: Chunking, Simulating Future Context and Decoding for Streaming ASRCode0
Pretraining without Wordpieces: Learning Over a Vocabulary of Millions of Words—0
NetKet 3: Machine Learning Toolbox for Many-Body Quantum SystemsCode1
tsflex: flexible time series processing & feature extractionCode1
Shallow Parsing for Nepal Bhasa Complement Clauses—0
Prepare your video for streaming with Segue—0
Unsupervised Chunking as Syntactic Structure Induction with a Knowledge-Transfer ApproachCode0
Deep Learning Transformer Architecture for Named Entity Recognition on Low Resourced Languages: State of the art results—0
Importance Estimation from Multiple Perspectives for Keyphrase Extraction—0
BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control CommunicationsCode1
A Review on Part-of-Speech Technologies—0
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design—0
Learning Structure from the Ground up---Hierarchical Representation Learning by Chunking—0
Paradigm Shift in Natural Language ProcessingCode1
Evaluating Relaxations of Logic for Neural Networks: A Comprehensive StudyCode0
Large-scale image segmentation based on distributed clustering algorithmsCode0
Neural Supervised Domain Adaptation by Augmenting Pre-trained Models with Random Units—0
Weighted Training for Cross-Task LearningCode0
Improving Named Entity Recognition by External Context Retrieving and Cooperative LearningCode1
Chunking Historical GermanCode0
Neural Sequence Segmentation as Determining the Leftmost SegmentsCode0
On the Hidden Negative Transfer in Sequential Transfer Learning for Domain Adaptation from News to Tweets—0
Locally-Contextual Nonlinear CRFs for Sequence Labeling—0
Evaluation of Morphological Embeddings for the Russian Language—0
Introducing the Hidden Neural Markov Chain framework—0
Highly Fast Text Segmentation With Pairwise Markov Chains—0
Unsupervised Technical Domain Terms Extraction using Term ExtractorCode1
Segmenting Natural Language Sentences via Lexical Unit Analysis—0
A Survey on Recent Advances in Sequence Labeling from Deep Learning Models—0
Enhance Robustness of Sequence Labelling with Masked Adversarial Training—0
Does Chinese BERT Encode Word Structure?Code0
Automated Concatenation of Embeddings for Structured PredictionCode1
Dissecting Span Identification Tasks with Performance Prediction—0
More Embeddings, Better Sequence Labelers?—0
AIN: Fast and Accurate Sequence Labeling with Approximate Inference NetworkCode1
Transparency and granularity in the SP Theory of Intelligence and its realisation in the SP Computer Model—0
To compress or not to compress? A Finite-State approach to Nen verbal morphology—0
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All datasetsCoNLL-2000Penn TreebankCoNLL 2003 (German)CoNLL 2003 (English)CoNLL 2003

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACEExact Span F197.3—Unverified
2BERT-CRF (Replicated in AdaSeq)Exact Span F197.18—Unverified
3ELMo + MAT + Multi-TaskExact Span F197.04—Unverified
4CVT+Multi-Task+LargeExact Span F196.98—Unverified
5ELMo + Multi-TaskExact Span F196.83—Unverified
6FlairExact Span F196.72—Unverified
7SeqVATExact Span F195.45—Unverified
8Adversarial TrainingExact Span F195.25—Unverified
9BiLSTM-CRFExact Span F195.18—Unverified
#ModelMetricClaimedVerifiedStatus
1ACEF1 score97.3—Unverified
2Flair embeddingsF1 score96.72—Unverified
3JMTF1 score95.77—Unverified
4Low supervisionF1 score95.57—Unverified
5IntNet + BiLSTM-CRFF1 score95.29—Unverified
6Suzuki and IsozakiF1 score95.15—Unverified
7NCRF++F1 score95.06—Unverified
8BI-LSTM-CRF (Senna) (ours)F1 score94.46—Unverified
#ModelMetricClaimedVerifiedStatus
1ACEF195—Unverified
2Wang et al., 2020F194.4—Unverified
3AINF194.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Wang et al., 2020F192—Unverified
2AINF191.71—Unverified
#ModelMetricClaimedVerifiedStatus
1Def2VecAUC93.07—Unverified