Open information extraction from the web
US8938410B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2010 |
| Grant date | Jan 20, 2015 |
| Priority date | — |
| Expiry date | Apr 16, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q10/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
To implement open information extraction, a new extraction paradigm has been developed in which a system makes a single data-driven pass over a corpus of text, extracting a large set of relational tuples without requiring any human input. Using training data, a Self-Supervised Learner employs a parser and heuristics to determine criteria that will be used by an extraction classifier (or other ranking model) for evaluating the trustworthiness of candidate tuples that have been extracted from the corpus of text, by applying heuristics to the corpus of text. The classifier retains tuples with a sufficiently high probability of being trustworthy. A redundancy-based assessor assigns a probability to each retained tuple to indicate a likelihood that the retained tuple is an actual instance of a relationship between a plurality of objects comprising the retained tuple. The retained tuples comprise an extraction graph that can be queried for information.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.