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 176–200 of 447 papers

TitleStatusHype
CarbonChat: Large Language Model-Based Corporate Carbon Emission Analysis and Climate Knowledge Q&A System—0
Domain Adaptation with Filtering for Named Entity Extraction of Japanese Anime-Related Words—0
Fine-tuned vs. Prompt-tuned Supervised Representations: Which Better Account for Brain Language Representations?—0
BIT-Xiaomi’s System for AutoSimTrans 2022—0
CausalRAG: Integrating Causal Graphs into Retrieval-Augmented Generation—0
Apprentissage automatique d'un chunker pour le fran (Machine Learning of a chunker for French) [in French]—0
Forgetting Exceptions is Harmful in Language Learning—0
From Dionysius Emerges Apollo -- Learning Patterns and Abstractions from Perceptual Sequences—0
From Finite-State to Inversion Transductions: Toward Unsupervised Bilingual Grammar Induction—0
Advanced System Integration: Analyzing OpenAPI Chunking for Retrieval-Augmented Generation—0
From Imitation to Refinement -- Residual RL for Precise Assembly—0
CHORUS: Zero-shot Hierarchical Retrieval and Orchestration for Generating Linear Programming Code—0
Generalization of metric classification algorithms for sequences classification and labelling—0
At a Glance: The Impact of Gaze Aggregation Views on Syntactic Tagging—0
Graph- and surface-level sentence chunking—0
Improving cross-lingual model transfer by chunking—0
Application of Prize based on Sentence Length in Chunk-based Automatic Evaluation of Machine Translation—0
Habits of Mind: Reusing Action Sequences for Efficient Planning—0
Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling—0
Document Chunking and Learning Objective Generation for Instruction Design—0
Hidden Markov tree models for semantic class induction—0
Hierarchical Recurrent Neural Network for Document Modeling—0
Hierarchical Word Structure-based Parsing: A Feasibility Study on UD-style Dependency Parsing in Japanese—0
Hierarchical Working Memory and a New Magic Number—0
A Data Efficient End-To-End Spoken Language Understanding Architecture—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