A system for entering information provided in a natural language sentence to a database or to a form provided on a computing device, the natural language sentence comprising a sequence of tokens, the system comprising: an encoder neural network configured to encode the sequence of tokens () in a set of vectors; a contextualization layer configured to generate a contextualized representation of the sequence of tokens from the set of vectors; a dimension-preserving convolutional neural network configured to employ the contextualized representation to generate output corresponding to a matrix; and a graph convolutional neural network configured to employ the matrix as a set of adjacency matrices, wherein the system is further configured to generate a label for each token in the sequence of tokens () based on hidden states for the token in the last layer of the graph convolutional neural network, wherein the encoder neural network, the contextualization layer, and the dimension-preserving convolutional neural network form a graph construction pipeline, wherein the matrix defines a graph structure which is a latent variable of the graph construction pipeline, wherein the system further comprises: a database interface configured to enter a token from the sequence of tokens () into the database, wherein entering the token comprises employing the label of the token as a key, wherein the graph convolutional neural network is trained with a graph-based learning algorithm for locating, in the sequence of tokens (), tokens that correspond to respective labels of a set of predefined labels, or a form interface configured to enter, into at least one slot of the form provided on the computing device, a token from the sequence of tokens (), wherein the label of the token identifies the slot, wherein the graph convolutional neural network is trained with a graph-based learning algorithm for tagging tokens of the sequence of tokens () with labels. an encoder neural network configured to encode the sequence of tokens () in a set of vectors; a contextualization layer configured to generate a contextualized representation of the sequence of tokens from the set of vectors; a dimension-preserving convolutional neural network configured to employ the contextualized representation to generate output corresponding to a matrix; and a graph convolutional neural network configured to employ the matrix as a set of adjacency matrices, wherein the system is further configured to generate a label for each token in the sequence of tokens () based on hidden states for the token in the last layer of the graph convolutional neural network, wherein the encoder neural network, the contextualization layer, and the dimension-preserving convolutional neural network form a graph construction pipeline, wherein the matrix defines a graph structure which is a latent variable of the graph construction pipeline, wherein the system further comprises: a database interface configured to enter a token from the sequence of tokens () into the database, wherein entering the token comprises employing the label of the token as a key, wherein the graph convolutional neural network is trained with a graph-based learning algorithm for locating, in the sequence of tokens (), tokens that correspond to respective labels of a set of predefined labels, or a form interface configured to enter, into at least one slot of the form provided on the computing device, a token from the sequence of tokens (), wherein the label of the token identifies the slot, wherein the graph convolutional neural network is trained with a graph-based learning algorithm for tagging tokens of the sequence of tokens () with labels. a database interface configured to enter a token from the sequence of tokens () into the database, wherein entering the token comprises employing the label of the token as a key, wherein the graph convolutional neural network is trained with a graph-based learning algorithm for locating, in the sequence of tokens (), tokens that correspond to respective labels of a set of predefined labels, or a form interface configured to enter, into at least one slot of the form provided on the computing device, a token from the sequence of tokens (), wherein the label of the token identifies the slot, wherein the graph convolutional neural network is trained with a graph-based learning algorithm for tagging tokens of the sequence of tokens () with labels.