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 401–447 of 447 papers

TitleStatusHype
Hidden Markov tree models for semantic class induction—0
UZH in BioNLP 2013—0
Entailment: An Effective Metric for Comparing and Evaluating Hierarchical and Non-hierarchical Annotation Schemes—0
Unsupervised Transduction Grammar Induction via Minimum Description Length—0
A Boosted Semi-Markov Perceptron—0
Investigation of annotator's behaviour using eye-tracking data—0
Segmentation Strategies for Streaming Speech Translation—0
Symbolic and statistical learning for chunking : comparison and combinations (Apprentissage symbolique et statistique pour le chunking:comparaison et combinaisons) [in French]—0
ClearTK-TimeML: A minimalist approach to TempEval 2013—0
Combining Top-down and Bottom-up Search for Unsupervised Induction of Transduction Grammars—0
Compound Embedding Features for Semi-supervised Learning—0
Automatic Morphological Enrichment of a Morphologically Underspecified Treebank—0
Using Constraint Grammar for Chunking—0
Obituary: George A. Miller—0
From Finite-State to Inversion Transductions: Toward Unsupervised Bilingual Grammar Induction—0
Semi-supervised Representation Learning for Domain Adaptation using Dynamic Dependency Networks—0
A Unified Framework for Discourse Argument Identification via Shallow Semantic Parsing—0
Noun Group and Verb Group Identification for Hindi—0
A Conditional Random Field-based Traditional Chinese Base Phrase Parser for SIGHAN Bake-off 2012 Evaluation—0
Sentence Parsing with Double Sequential Labeling in Traditional Chinese Parsing Task—0
A Model of Vietnamese Person Named Entity Question Answering System—0
Exploiting Chunk-level Features to Improve Phrase Chunking—0
Subgroup Detector: A System for Detecting Subgroups in Online Discussions—0
A Cost Sensitive Part-of-Speech Tagging: Differentiating Serious Errors from Minor Errors—0
Improving Statistical Machine Translation through co-joining parts of verbal constructs in English-Hindi translation—0
Building Trainable Taggers in a Web-based, UIMA-Supported NLP Workbench—0
Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection—0
Simultaneous error detection at two levels of syntactic annotation—0
A Reranking Model for Discourse Segmentation using Subtree Features—0
Apprentissage automatique d'un chunker pour le fran (Machine Learning of a chunker for French) [in French]—0
Enrichir et raisonner sur des espaces s\'emantiques pour l'attribution de mots-cl\'es (Enriching and reasoning on semantic spaces for keyword extraction) [in French]—0
Un segmenteur-\'etiqueteur et un chunker pour le fran (A Segmenter-POS Labeller and a Chunker for French) [in French]—0
Deep Unsupervised Feature Learning for Natural Language Processing—0
La structuration prosodique et les relations syntaxe/ prosodie dans le discours politique (Prosodic Structuring and the Syntax-Prosody Relationship in Political Speech) [in French]—0
Detecting Japanese Compound Functional Expressions using Canonical/Derivational Relation—0
ROMBAC: The Romanian Balanced Annotated Corpus—0
A Concise Query Language with Search and Transform Operations for Corpora with Multiple Levels of Annotation—0
YADAC: Yet another Dialectal Arabic Corpus—0
Open-Source Boundary-Annotated Corpus for Arabic Speech and Language Processing—0
Improving the Recall of a Discourse Parser by Constraint-based Postprocessing—0
Predicting Phrase Breaks in Classical and Modern Standard Arabic Text—0
PHACTS about activation-based word similarity effects—0
Linguistically-Adapted Structural Query Annotation for Digital Libraries in the Social Sciences—0
Multi-View Learning of Word Embeddings via CCA—0
Named Entity Recognition in Tweets: An Experimental StudyCode0
Natural Language Processing (almost) from ScratchCode0
Forgetting Exceptions is Harmful in Language Learning—0
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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