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Semantic Annotation for Tabular Data with DBpedia: Adapted SemTab 2019 with DBpedia 2016-10

Authors: Nguyen, Phuc; Kertkeidkachorn, Natthawut; Ichise, Ryutaro; Takeda, Hideaki;

Semantic Annotation for Tabular Data with DBpedia: Adapted SemTab 2019 with DBpedia 2016-10

Abstract

Semantic Annotation for Tabular Data with DBpedia: Adapted SemTab 2019 with DBpedia 2016-10 Github: https://github.com/phucty/mtab4dbpedia --------------------------------------------------------------------------------------------------------------------------------------- CEA: Keep only valid entities in DBpedia 2016-10 Resolve percentage encoding Add missing redirect entities CTA: Keep only valid types Resolve transitive types (parents and equivalent types of the specific type) with DBpedia ontology 2016-10 CPA: Add equivalent properties Statistic of Adapted Tabular data SemTab 2019 | | CEA | | | CPA | | | CTA | | | |---------|:--------:|:-------:|:------:|:--------:|:-------:|:------:|:--------:|---------|--------| | | Orginal | Adapted | Change | Orginal | Adapted | Change | Orginal | Adapted | Change | | Round 1 | 8418 | 8406 | -0.14% | 116 | 116 | 0.00% | 120 | 120 | 0.00% | | Round 2 | 463796 | 457567 | -1.34% | 6762 | 6762 | 0.00% | 14780 | 14333 | -3.02% | | Round 3 | 406827 | 406820 | 0.00% | 7575 | 7575 | 0.00% | 5762 | 5673 | -1.54% | | Round 4 | 107352 | 107351 | 0.00% | 2747 | 2747 | 0.00% | 1732 | 1717 | -0.87% | --------------------------------------------------------------------------------------------------------------------------------------- DBpedia 2016-10 extra resources: (Original dataset http://downloads.dbpedia.org/2016-10/) --------------------------------------------------------------------------------------------------------------------------------------- File: _dbpedia_classes_2016-10.csv Information: DBpedia classes and parents: (We remove the abstract types: Agent, Thing) Total: 759 classes Structure: [class, parents (separate with space)] (without prefix dbo: or http://dbpedia.org/ontology/) Example: "City","Location Place PopulatedPlace Settlement" --------------------------------------------------------------------------------------------------------------------------------------- File: _dbpedia_properties_2016-10.csv Information: DBpedia properties and these equivalents Total: 2865 properties Structure: [property, it’s equivalent properties] (without prefix dbo: or http://dbpedia.org/ontology/) Example: "restingDate","deathDate" --------------------------------------------------------------------------------------------------------------------------------------- File: _dbpedia_domains_2016-10.csv Information: DBpedia properties and these domain types Total: 2421 properties (have types as their domain) Structure: [property, type (domain)] (without prefix dbo: or http://dbpedia.org/ontology/) Example: "deathDate","Person" --------------------------------------------------------------------------------------------------------------------------------------- File: _dbpedia_entities_2016-10.jsonl.bz2 Information: DBpedia entity dump Format: json list bz2 (bz2 Compressed json list) Source: DBpedia dump 2016-10 core Total: 5,289,577 entities (No disambiguation entities) Structure: An entity: for example “Tokyo”: (datatype: dictionary), { 'wd': 'Q1322032', (Wikidata ID, datatype: string) 'wp': 'Tokyo', (Wikipedia ID, add prefix https://en.wikipedia.org/wiki/ + wp to get the Wikipedia URL, datatype: string) 'dp': 'Tokyo', (DBpedia ID, add prefix http://dbpedia.org/resource/ + dp to get the DBpedia URL, datatype: string) 'label': 'Tokyo', (Entity label, datatype: string) 'aliases': ['To-kyo', 'Tôkyô Prefecture', ..], (Other entity names, datatype: list) 'aliases_multilingual': ['东京小子', 'طوكيو', ...], (Other entity names in multilingual, datatype: list) 'types_specific': 'City', (Entity direct type, datatype: string) 'types_transitive': ['Human settlement', 'City', 'PopulatedPlace', 'Location', 'Place', 'Settlement'], (Entity transitive types, datatype: list) 'claims_entity': { (entity statements, datatype: dictionary. Keys: properties, Values: list of tail entities) 'governingBody': ['Tokyo Metropolitan Government'], 'subdivision': ['Honshu', 'Kantō region'], ... }, 'claims_literal': { 'string': { (String literal: datatype: dictionary. Keys: properties, Values: list of values 'postalCode': ['JP-13'], 'utcOffset': ['+09:00', '+9'], … } 'time': { (Time literal: datatype: dictionary. Keys: properties, Values: list of date time 'populationAsOf': ['2016-07-31'], ... }), 'quantity': { (Numerical literal: datatype: dictionary. Keys: properties, Values: list of values populationDesity: [6224.66, 6349.0], 'maximumElevation': [2017], ... }, 'pagerank': 2.2167366040153352e-06 (Entity page rank score calculated on DBpedia Graph) } --------------------------------------------------------------------------------------------------------------------------------------- THIS DATA IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

This data is redistributed from - SemTab 2019: https://doi.org/10.5281/zenodo.3518530 - Wikipedia https://www.wikipedia.org/ - DBpedia http://dbpedia.org/ - T2Dv2 Gold Standard for Matching Web Tables to DBpedia http://webdatacommons.org/webtables/goldstandardV2.html Please refer to the licenses from these sources.

Keywords

tables, tabular data, dbpedia, column-type matching, cell-entity matching, semantic annotation, column relation-property matching

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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