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== Neural period ==
[[File:A_development_of_natural_language_processing_tools.png|thumb|Timeline of natural language processing models]]
In 1990, the [[Recurrent neural network#Elman networks and Jordan networks|Elman network]], using a [[recurrent neural network]], encoded each word in a training set as a vector, called a [[word embedding]], and the whole vocabulary as a [[vector database]], allowing it to perform such tasks as sequence-predictions that are beyond the power of a simple [[multilayer perceptron]]. A shortcoming of the static embeddings was that they didn't differentiate between multiple meanings of [[Homonym|homonyms]].<ref name="1990_ElmanPaper">{{cite journal |last=Elman |first=Jeffrey L. |date=March 1990 |title=Finding Structure in Time |url=http://doi.wiley.com/10.1207/s15516709cog1402_1 |journal=Cognitive Science |volume=14 |issue=2 |pages=179–211 |doi=10.1207/s15516709cog1402_1 |s2cid=2763403|url-access=subscription }}</ref>
==Software==
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