Introduction to the CoNLL-2000 Shared Task Chunking

By E. Tjong Kim Sang, Sabine Buchholz. 2000

974 citations recorded by the source corpus.

We describe the CoNLL-2000 shared task: dividing text into syntactically related non-overlapping groups of words, so-called text chunking. We give background information on the data sets, present a general overview of the systems that have taken part in the shared task and briefly discuss their performance.

Subfields: General Health Professions, Natural Language Processing, Philosophy

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Citations in the corpus

Semi-Supervised Sequence Modeling with Cross-View Training (2018, methodology): “Text Chunking : We use the CoNLL-2000 data (Tjong Kim Sang and Buchholz, 2000).”
Dissecting Contextual Word Embeddings: Architecture and Representation (2018, methodology): “Figure 2 shows a t-SNE (Maaten and Hinton, 2008) visualization of span representations of 3,000 labeled chunks and 500 spans not labeled as chunks from the CoNLL 2000 chunking dataset (Sang and Buchholz, 2000), from the first layer of the 4-layer LSTM.”
Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs (2016, methodology): “CoNLL The CoNLL dataset released by Tjong Kim Sang & Buchholz (2000) poses the task of text chunking.”
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers (2020, methodology): “We randomly pick labeled chunks and unlabeled spans from the CoNLL 2000 chunking dataset [34], and extract span representations from each layer of the 6x384”
Datasets: A Community Library for Natural Language Processing (2021, neutral): “Tasks like CoNLL 2000 (Tjong Kim Sang and Buchholz, 2000) continue to be widely used more than 20 years after their release.”
Linguistic Knowledge and Transferability of Contextual Representations (2019, methodology): “We use the CoNLL 2000 shared task dataset (Tjong Kim Sang and Buchholz, 2000).”
What Does BERT Learn about the Structure of Language? (2019, methodology): “We randomly pick 3000 labeled chunks and 500 spans not labeled as chunks from the CoNLL 2000 chunking dataset (Sang and Buchholz, 2000).”
Deep multi-task learning with low level tasks supervised at lower layers (2016, background): “, POS tags as features for syntactic chunking (Sang and Buchholz, 2000) or parsing (Nivre et al.”
Hybrid Deterministic-Stochastic Methods for Data Fitting (2011, methodology): “…CRF experiments, we use the noun-phrase chunking problem from the CoNLL-2000 Shared Task [31], where the goal is to assign each word in a sentence to one of 22 possible states, and we use approximately 1.6 million features to represent the presence of words and word combinations [31, 32].”
FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP (2019, background): “, 2006) en default, fast NP Chunking CoNLL 2000 (Sang and Buchholz, 2000) en default, fast Offensive Language Detection GermEval 2018 (Wiegand et al.”
Exploring and Predicting Transferability across NLP Tasks (2020, methodology): “Sequence labeling (eleven tasks): We experiment with eleven sequence labeling tasks used by Liu et al. (2019a), including CCG supertagging with CCGbank (CCG; Hockenmaier and Steedman, 2007); part-of-speech tagging with the Penn Treebank (POS-PTB; Marcus et al., 1993) and the Universal Dependencies E”