ABCDEFGHIJKLMNOPQRST
1
2
3
TitleUnsupervised Extraction and Publication of Linked Entities and Hypernyms
4
5
AuthorsMilan DojchinovskiTomas Kliegr
6
Web Engineering Group Department of Information and Knowledge Engineering
7
Faculty of Information Technology Czech Technical University in PragueFaculty of Informatics and Statistics
University of Economics, Prague, Czech Republic
8
milan.dojchinovski@fit.cvut.cztomas.kliegr@vse.cz
9
http://dojchinovski.mkhttps://sites.google.com/site/kliegr/
10
11
AbstractEasy extraction and access to an information from a semi- structured textual documents is still a challenge. In this paper, we present a method for effective extraction of entities as well as a way of publishing such information in a machine-readable RDF/OWL -based format based on the four Linked Data principles. Using our approach the users, as well as the other tools, can share the NLP processed results among each other. We present the architecture of the tool implemented as a web application and an API. We validate our tool on a real dataset, and show the effectiveness of the approach in comparison to other existing NER tools.
12
13
KeywordsNamed Entity Extractors, Linked Data, Link Discovery
14
15
WWWhttp://ner.vse.cz/thd
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100