| P10-1030 | that -- with new techniques -- | self-supervised learning | of relation-specific extractors |
| Q15-1009 | 2012 ) ) . They often perform | self-supervised learning | of relation-independent ex - |
| W10-0911 | conquering the long tail via a | self-supervised learning | pro- cess . This self-supervision |
| W10-0911 | representation , bootstrap - ping , | self-supervised learning | , large-scale joint in - ference |
| P10-1013 | performance is a novel form of | self-supervised learning | for open extractors -- using |
| P10-1013 | approach to open IE that uses | self-supervised learning | over unlexicalized features , |
| W10-0911 | tail of textual knowledge via a | self-supervised learning | process that leverages data redundancy |
| D11-1134 | deep linguistic parser to perform | self-supervised learning | and extracts a positive set ( |
| P10-1030 | ( Freitag , 1998 ) . Open IE , | self-supervised learning | of unlexicalized , relation-independent |
| W09-1605 | where the main goal is to use | self-supervised learning | to align or/and create new Wikipedia |
| C02-1148 | respectively . Finally , for the | self-supervised learning | technique , by controlling the |
| W10-0911 | and conquer the long tail in a | self-supervised learning | process that raises certainty |
| W10-0911 | ones . To do machine reading , a | self-supervised learning | process , informed by meta knowledege |
| P13-1063 | corresponding article texts by using a | self-supervised learning | method ( Wu and Weld , 2007 ) |
| W15-2612 | knowledge . Distant supervision ( | self-supervised learning | ) is a widely applied technique |
| W10-0911 | representation and joint inference ; | Self-supervised learning | is governed by a joint probabilistic |
