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An Ontology-Driven Probabilistic Soft Logic Approach to Improve NLP Entity Annotations
Published on Nov 22, 20183813 Views
Many approaches for Knowledge Extraction and Ontology Population rely on well-known Natural Language Processing (NLP) tasks, such as Named Entity Recognition and Classification (NERC) and Entity Linki
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An Ontology-Driven Probabilistic Soft Logic Approach to Improve NLP Entity Annotations00:00
Context: Knowledge Extraction - 100:18
Context: Knowledge Extraction - 200:30
Context: Knowledge Extraction - 300:32
Context: Knowledge Extraction - 400:49
Context: Knowledge Extraction - 500:58
Motivating Examples - 101:32
Motivating Examples - 201:41
Motivating Examples - 301:43
Motivating Examples - 401:51
Motivating Examples - 502:04
Motivating Examples - 602:09
Abstracting - 102:18
Abstracting - 202:25
Abstracting - 302:26
Abstracting - 402:33
Abstracting - 502:44
Abstracting - 602:51
Research problem03:01
In a nutshell - 103:09
In a nutshell - 203:30
In a nutshell - 303:35
In a nutshell - 403:38
In a nutshell - 504:07
Contributions04:15
Probabilistic Soft Logic04:57
Probabilistic Soft Logic in a nutshell (1/3) - 105:02
Probabilistic Soft Logic in a nutshell (1/3) - 205:38
Probabilistic Soft Logic in a nutshell (1/3) - 305:49
Probabilistic Soft Logic in a nutshell (1/3) - 406:00
Probabilistic Soft Logic in a nutshell (1/3) - 506:14
Probabilistic Soft Logic in a nutshell (2/3) - 106:32
Probabilistic Soft Logic in a nutshell (2/3) - 207:08
Probabilistic Soft Logic in a nutshell (2/3) - 307:14
Probabilistic Soft Logic in a nutshell (3/3) - 407:24
Probabilistic Soft Logic in a nutshell (3/3) - 507:29
Probabilistic Soft Logic in a nutshell (3/3) - 607:40
psl4ea08:14
1. Classes implied by NLP annotations - 108:35
1. Classes implied by NLP annotations - 209:17
1. Classes implied by NLP annotations - 309:42
1. Classes implied by NLP annotations - 410:01
1. Classes implied by NLP annotations - 510:11
1. Classes implied by NLP annotations - 610:16
1. Classes implied by NLP annotations - 710:44
1. Classes implied by NLP annotations - 811:23
1. Classes implied by NLP annotations - 911:25
1. Classes implied by NLP annotations - 1011:38
1. Classes implied by NLP annotations - 1111:58
2. Annotation Coherence via Classes - 112:07
2. Annotation Coherence via Classes - 212:22
MPE Inference13:25
Application and Evaluation14:14
Background Knowledge14:17
Tools14:22
NERC+EL Datasets - 114:28
NERC+EL Datasets - 214:32
Research Question - 114:53
Research Question - 215:06
Results - 115:14
Results - 215:42
Results - 315:51
Research Question - 115:58
Research Question - 216:00
Conclusions16:03
Marco Rospocher17:03