RIGHTS MAPPING SYSTEM AND METHOD
A method and system can include processing title and title opinion document images to generate text information. Trained models may generate data objects representative of period of time during which certain rights to a property exist. The trained models may also generate rules for modifying the data objects and interrelating the data objects to each other. In some examples, a confidence level can be generated and will reflect a likelihood of a data object including correct information. The modified and interrelated data objects may be used to generate a navigable interface which includes a current title status for a property and a navigable chain of title reflecting historical rights to the property.
1 . A method comprising:
accessing, from a database and by a processing device, one or more electronic documents corresponding to a property;
extracting text from the one or more electronic documents comprising ownership interest in the property;
generating, using a machine-trained model, a plurality of data objects comprising a description of a property right to the property, the description comprising the extracted text from the one or more electronic documents;
determining, using the machine-trained model, a relationship between each of the plurality of data objects;
determining, using the machine-trained model, a confidence level for each of the plurality of data objects by:
determining a number of supporting title documents in the one or more electronic documents from which the text is extracted; and
validating the supporting title documents; and
displaying, on a display device and based on the determined confidence levels, the plurality of data objects and the determined relationship between each of the plurality of data objects.
2 . The method of claim 1 , wherein the confidence level for each of the plurality of data objects is further determined by the inclusion of a title opinion document in the one or more electronic documents, the title opinion document associated with the extracted text of a corresponding data object.
3 . The method of claim 1 , wherein each of the plurality of data objects is associated with one of four possible confidence levels.
4 . The method of claim 1 , wherein the relationship between each of the plurality of data objects is based on the determined confidence level for each of the plurality of data objects.
5 . The method of claim 1 , wherein each of the plurality of data objects further comprise a current property right, a length of time, an identifier of the location, and a corresponding document of the one or more electronic documents.
6 . The method of claim 1 , further comprising:
generating, by the processing device, text of the one or more electronic documents by executing an optical character recognition (OCR) process on the one or more electronic documents.
7 . The method of claim 1 , further comprising:
determining, using the machine-trained model, a confidence level for a most recent data object of the plurality of data objects with a most recently obtained electronic document.
8 . The method of claim 7 , wherein the most recently obtained electronic document is determined by a date text extracted from the most recently obtained electronic document and associated with the most recent data object.
9 . The method of claim 1 further comprising:
displaying a navigable interface comprising one or more nodes connected by edges, each node associated with one of the plurality of data objects and each edge associated with a transition from a first data object to a second data object, the transition associated with a change in property rights to the property.
10 . The method of claim 9 , wherein an edge of the navigable interface corresponding to the confidence level is color coded according to a confidence level value associated with the first data object and the second data object.
11 . A system comprising:
one or more hardware processors; and
a memory comprising instructions operable by the one or more hardware processors to:
access, from a database, one or more electronic documents corresponding to a property;
extract text from the one or more electronic documents comprising ownership interest in the property;
generate, using a machine-trained model, a plurality of data objects comprising a description of a property right to the property, the description comprising the extracted text from the one or more electronic documents;
determine, using the machine-trained model, a relationship between each of the plurality of data objects;
determine, using the machine-trained model, a confidence level for each of the plurality of data objects by:
determine a number of supporting title documents in the one or more electronic documents from which the text is extracted; and
validate the supporting title documents; and
display, on a display device and based on the determined confidence levels, the plurality of data objects and the determined relationship between each of the plurality of data objects.
12 . The system of claim 11 , wherein the confidence level for each of the plurality of data objects is further determined by the inclusion of a title opinion document in the one or more electronic documents, the title opinion document associated with the extracted text of a corresponding data object.
13 . The system of claim 11 , wherein each of the plurality of data objects is associated with one of four possible confidence levels.
14 . The system of claim 11 , wherein the relationship between each of the plurality of data objects is based on the determined confidence level for each of the plurality of data objects.
15 . The system of claim 11 , wherein each of the plurality of data objects further comprise a current property right, a length of time, an identifier of the location, and a corresponding document of the one or more electronic documents.
16 . The system of claim 11 , wherein the instructions cause the one or more hardware processors to further:
generate text of the one or more electronic documents by executing an optical character recognition (OCR) process on the one or more electronic documents.
17 . The system of claim 11 , wherein the instructions cause the one or more hardware processors to further:
determine, using the machine-trained model, a confidence level for a most recent data object of the plurality of data objects with a most recently obtained electronic document.
18 . The system of claim 17 , wherein the most recently obtained electronic document is determined by a date text extracted from the most recently obtained electronic document and associated with the most recent data object.
19 . The system of claim 11 , wherein the instructions cause the one or more hardware processors to further:
display a navigable interface comprising one or more nodes connected by edges, each node associated with one of the plurality of data objects and each edge associated with a transition from a first data object to a second data object, the transition associated with a change in property rights to the property.
20 . The system of claim 19 , wherein an edge of the navigable interface corresponding to the confidence level is color coded according to a confidence level value associated with the first data object and the second data object.