Incorporating non-local information into information extraction systems by Gibbs sampling

Jenny Rose Finkel; Trond Grenager; Christopher D. Manning

doi:https://doi.org/10.3115/1219840.1219885

Incorporating non-local information into information extraction systems by Gibbs sampling

2005 · 3,044 citations · 6 from inside this corpus

Jenny Rose Finkel, Trond Grenager low, Christopher D. Manning

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

11 of 11 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.

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Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

The Stanford CoreNLP Natural Language Processing Toolkit→Incorporating non-local information into information extraction systems by Gibbs samplingLegacy edge — source detail unavailable
Knowledge Graph Embedding by Translating on Hyperplanes→Incorporating non-local information into information extraction systems by Gibbs samplingLegacy edge — source detail unavailable
Bidirectional LSTM-CRF Models for Sequence Tagging→Incorporating non-local information into information extraction systems by Gibbs samplingLegacy edge — source detail unavailable
Distant supervision for relation extraction without labeled data→Incorporating non-local information into information extraction systems by Gibbs samplingLegacy edge — source detail unavailable
Knowledge Graphs→Incorporating non-local information into information extraction systems by Gibbs samplingLegacy edge — source detail unavailable
Design challenges and misconceptions in named entity recognition→Incorporating non-local information into information extraction systems by Gibbs samplingLegacy edge — source detail unavailable
Incorporating non-local information into information extraction systems by Gibbs sampling→A tutorial on hidden Markov models and selected applications in speech recognitionLegacy edge — source detail unavailable
Incorporating non-local information into information extraction systems by Gibbs sampling→Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence DataLegacy edge — source detail unavailable
Incorporating non-local information into information extraction systems by Gibbs sampling→An Introduction to MCMC for Machine LearningLegacy edge — source detail unavailable
Incorporating non-local information into information extraction systems by Gibbs sampling→Simulated Annealing: Theory and ApplicationsLegacy edge — source detail unavailable
Incorporating non-local information into information extraction systems by Gibbs sampling→A Tutorial on Hidden Markov Models and Selected Applications in Speech RecognitionLegacy edge — source detail unavailable
Bidirectional LSTM-CRF Models for Sequence Tagging→A tutorial on hidden Markov models and selected applications in speech recognitionLegacy edge — source detail unavailable
Bidirectional LSTM-CRF Models for Sequence Tagging→Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence DataLegacy edge — source detail unavailable
Design challenges and misconceptions in named entity recognition→A tutorial on hidden Markov models and selected applications in speech recognitionLegacy edge — source detail unavailable
Design challenges and misconceptions in named entity recognition→Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence DataLegacy edge — source detail unavailable
Design challenges and misconceptions in named entity recognition→A Tutorial on Hidden Markov Models and Selected Applications in Speech RecognitionLegacy edge — source detail unavailable
An Introduction to MCMC for Machine Learning→Simulated Annealing: Theory and ApplicationsLegacy edge — source detail unavailable
Knowledge Graph Embedding by Translating on Hyperplanes→Distant supervision for relation extraction without labeled dataLegacy edge — source detail unavailable
Knowledge Graphs→Design challenges and misconceptions in named entity recognitionLegacy edge — source detail unavailable
Knowledge Graphs→Distant supervision for relation extraction without labeled dataLegacy edge — source detail unavailable
Knowledge Graphs→Knowledge Graph Embedding by Translating on HyperplanesLegacy edge — source detail unavailable

What this paper cites, inside the corpus

Paper	Year	Cited
A tutorial on hidden Markov models and selected applications in speech recognition	1989	22,910
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data	2001	12,994
An Introduction to MCMC for Machine Learning	2003	2,430
Simulated Annealing: Theory and Applications	1987	2,384
A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition	1990	1,889

What cites it, inside the corpus

Paper	Year	Cited
The Stanford CoreNLP Natural Language Processing Toolkit	2014	7,269
Knowledge Graph Embedding by Translating on Hyperplanes	2014	3,838
Bidirectional LSTM-CRF Models for Sequence Tagging	2015	3,287
Distant supervision for relation extraction without labeled data	2009	2,924
Knowledge Graphs	2021	1,767
Design challenges and misconceptions in named entity recognition	2009	1,491

Links

Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record

Topics

Topic Modeling	Computer Science
Machine Learning and Algorithms	Computer Science
Natural Language Processing Techniques	Computer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

supports3 author record(s) attached.
supports25 reference(s) recorded.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:47+00:00.

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