Systems and methods for determining structured proceeding outcomes

An apparatus configured to identify an outcome of a structured proceeding, the apparatus comprising:

• a processor;
• a memory coupled to the processor, wherein the memory comprises a deep learning classifier, and wherein the deep learning classifier is configured to:
• receive, at a first level of a neural network of the deep learning classifier, a first word token corresponding to a first word of a first entry of the structured proceeding;
• receive, at the first level of the neural network, a second word token corresponding to a first word of a second entry of the structured proceeding, wherein the first level of the neural network comprises a first plurality of bidirectional gated recurrent units (GRUs) and a second plurality of GRUs;
• output, by the first plurality of GRUs, a first encoded entry corresponding to the first entry of the structured proceeding;
• output, by the second plurality of GRUs, a second encoded entry corresponding to the second entry of the structured proceeding;
• receive, at a second level of the neural network of the deep learning classifier, the first encoded entry and the second encoded entry, wherein:
• the second level of the neural network includes a third plurality of GRUs, a first GRU of the third plurality of GRUs is coupled to the first plurality of GRUs and is configured to receive the first encoded entry, and
• a second GRU of the third plurality of GRUs is coupled to the second plurality of GRUs and is configured to receive the second encoded entry;
• and
• output, by the second level of the neural network, an encoded structured proceeding corresponding to the structured proceeding;
• receive, by a third level of the neural network of the deep learning classifier, the encoded structured proceeding;
• and
• output, by the third level of the neural network, a probability score associated with an outcome corresponding to the encoded structured proceeding.

A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to:

• receive, at a first level of a neural network of a deep learning classifier, a first word token corresponding to a first word of a first entry of a structured proceeding;
• receive, at the first level of the neural network, a second word token corresponding to a first word of a second entry of the structured proceeding, wherein the first level of the neural network comprises a first plurality of bidirectional gated recurrent units (GRUs) and a second plurality of GRUs;
• output, by the first plurality of GRUs, a first encoded entry corresponding to the first entry of the structured proceeding;
• output, by the second plurality of GRUs, a second encoded entry corresponding to the second entry of the structured proceeding;
• receive, at a second level of the neural network of the deep learning classifier, the first encoded entry and the second encoded entry, wherein:
• the second level of the neural network includes a third plurality of GRUs,
• a first GRU of the third plurality of GRUs is coupled to the first plurality of GRUs and is configured to receive the first encoded entry, and
• a second GRU of the third plurality of GRUs is coupled to the second plurality of GRUs and is configured to receive the second encoded entry;
• and
• output, by the second level of the neural network, an encoded structured proceeding corresponding to the structured proceeding;
• receive, by a third level of the neural network of the deep learning classifier, the encoded structured proceeding;
• and
• output, by the third level of the neural network, a probability score associated with an outcome corresponding to the encoded structured proceeding.