Invention Grant
- Patent Title: Autonomous open schema construction from unstructured text
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Application No.: US17587401Application Date: 2022-01-28
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Publication No.: US11977569B2Publication Date: 2024-05-07
- Inventor: Michael Lynn Potter , Natalie Lynn Larson , Amy Cheng , Hovanes Keseyan , Hanh Servin
- Applicant: The United States of America, as represented by the Secretary of the Navy
- Applicant Address: US IN Crane
- Assignee: The United States of America, Represented by the Secretary of the Navy
- Current Assignee: The United States of America, Represented by the Secretary of the Navy
- Current Assignee Address: US DC Washington
- Agency: Naval Surface Warfare Center, Crane Division
- Agent Patrick Law
- Main IPC: G06F16/00
- IPC: G06F16/00 ; G06F16/31 ; G06F16/33 ; G06F16/35 ; G06N3/044

Abstract:
Disclosed is a natural language processing pipeline that analyzes and processes a corpus of textual data to automatically create a knowledge graph containing the corpus entities such as subjects and object and their relationships such as predicates or verbs. The pipeline is configured as an end-to-end neural Open Schema Construction pipeline having a coreference resolution module, an open information extraction (OIE) module, and an entity canonicalization module. The processed textual data is input to a graph database to create the knowledge graph displayable through a graphical user interface. In operation, the pipeline modules serve to create a single term for all entity mentions in the corpus that reference the same entity through coreference resolution, extract all subject-predicate-object triplets from the coreference resolved corpus through OIE, and then canonicalize the corpus by clustering each entity mention to a canonical form for mapping to the knowledge graph and display.
Public/Granted literature
- US20220300544A1 AUTONOMOUS OPEN SCHEMA CONSTRUCTION FROM UNSTRUCTURED TEXT Public/Granted day:2022-09-22
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