Graphene is an information extraction pipeline which extracts Knowledge Graphs from texts (n-ary relations and rhetorical structures extracted from complex factoid discourse). Given a sentence or a text, Graphene outputs a semantic representation of the text which is a labeled directed graph (a knowledge graph). This knowledge graph can be later used for addressing different AI tasks, such as building Question Answering systems, extracting structured data from text, supporting semantic inference, among other tasks. Differently from existing open relation extraction tools, which focus on the main relation expressed in a sentence, Graphene aims at maximizing the extraction of contextual relations. For example:
Trump withdrew his sponsorship after the second Tour de Trump in 1990 because his business ventures were experiencing financial woes.
In order to capture all the contextual information, Graphene performs the following steps:
- Resolves co-references.
- Transforms complex sentences (for example, containing subordinations, coordinations, appositive phrases, etc), into simple independent sentences (one clause per sentence).
- Identifies rhetorical relations between those sentences
- Extract binary relations (
subject,predicateandobject) from each sentence. - Merge all the extracted relations into a relation graph (knowledge graph).
Graphene’s extracted graphs are represented by our RDFNL format, an simple format that facilitates the representation of complex contextual relations in a way that balances machine representation with human legibility. A description of the RDFNL format can be found here. In order to increase further processability of the extracted relations, Graphene can materialize its relations into a proper RDF graph serialized under the N-Triples specification of the RDF standard. A description of the RDF format can be found here. Alternatively, developers can use the direct output class of the API, which is serializable and deserializable as a JSON object.
The café arrived in Paris in the 17th century , when the beverage was first brought from Turkey , and by the 18th century Parisian cafés were centres of the city 's political and cultural life .
The serialized class: JSON
The RDFNL format:
# The café arrived in Paris in the 17th century , when the beverage was first brought from Turkey , and by the 18th century Parisian cafés were centres of the city 's political and cultural life .
3469c5159933484a8bbdb5b1df36136f 0 The café arrived in Paris in the 17th century
ELEM-BACKGROUND fcbcb5c547f248cc88f8aa3033178d12
fcbcb5c547f248cc88f8aa3033178d12 1 The beverage was first brought
VCON-SPATIAL from Turkey .
394d55aacc064bcc82912689dc0500b9 0 Parisian cafés were centres of the city 's political and cultural life
VCON-TEMPORAL by the 18th century .
The RDF N-Triples format:
# The café arrived in Paris in the 17th century , when the beverage was first brought from Turkey , and by the 18th century Parisian cafés were centres of the city 's political and cultural life .
_:65e72e14ff3f4e9bb173afd10a84050a <http://lambda3.org/graphene/sentence#original-text> "The café arrived in Paris in the 17th century , when the beverage was first brought from Turkey , and by the 18th century Parisian cafés were centres of the city 's political and cultural life ."^^<http://www.w3.org/2001/XMLSchema#string> .
_:65e72e14ff3f4e9bb173afd10a84050a <http://lambda3.org/graphene/sentence#has-extraction> _:fcbcb5c547f248cc88f8aa3033178d12 .
_:fcbcb5c547f248cc88f8aa3033178d12 <http://lambda3.org/graphene/extraction#subject> <http://lambda3.org/graphene/text#The+beverage> .
_:fcbcb5c547f248cc88f8aa3033178d12 <http://lambda3.org/graphene/extraction#predicate> <http://lambda3.org/graphene/text#was+first+brought> .
_:fcbcb5c547f248cc88f8aa3033178d12 <http://lambda3.org/graphene/extraction#object> <http://lambda3.org/graphene/text#> .
_:fcbcb5c547f248cc88f8aa3033178d12 <http://lambda3.org/graphene/extraction#context-layer> "1"^^<http://www.w3.org/2001/XMLSchema#integer> .
<http://lambda3.org/graphene/text#The+beverage> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "The beverage"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://lambda3.org/graphene/text#was+first+brought> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "was first brought"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://lambda3.org/graphene/text#> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> ""^^<http://www.w3.org/2001/XMLSchema#string> .
_:fcbcb5c547f248cc88f8aa3033178d12 <http://lambda3.org/graphene/extraction#VCON-SPATIAL> <http://lambda3.org/graphene/text#from+Turkey+.> .
<http://lambda3.org/graphene/text#from+Turkey+.> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "from Turkey ."^^<http://www.w3.org/2001/XMLSchema#string> .
_:65e72e14ff3f4e9bb173afd10a84050a <http://lambda3.org/graphene/sentence#has-extraction> _:3469c5159933484a8bbdb5b1df36136f .
_:3469c5159933484a8bbdb5b1df36136f <http://lambda3.org/graphene/extraction#subject> <http://lambda3.org/graphene/text#The+caf%C3%A9> .
_:3469c5159933484a8bbdb5b1df36136f <http://lambda3.org/graphene/extraction#predicate> <http://lambda3.org/graphene/text#arrived> .
_:3469c5159933484a8bbdb5b1df36136f <http://lambda3.org/graphene/extraction#object> <http://lambda3.org/graphene/text#in+Paris+in+the+17th+century> .
_:3469c5159933484a8bbdb5b1df36136f <http://lambda3.org/graphene/extraction#context-layer> "0"^^<http://www.w3.org/2001/XMLSchema#integer> .
<http://lambda3.org/graphene/text#The+caf%C3%A9> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "The café"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://lambda3.org/graphene/text#arrived> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "arrived"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://lambda3.org/graphene/text#in+Paris+in+the+17th+century> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "in Paris in the 17th century"^^<http://www.w3.org/2001/XMLSchema#string> .
_:3469c5159933484a8bbdb5b1df36136f <http://lambda3.org/graphene/extraction#ELEM-BACKGROUND> _:fcbcb5c547f248cc88f8aa3033178d12 .
_:65e72e14ff3f4e9bb173afd10a84050a <http://lambda3.org/graphene/sentence#has-extraction> _:394d55aacc064bcc82912689dc0500b9 .
_:394d55aacc064bcc82912689dc0500b9 <http://lambda3.org/graphene/extraction#subject> <http://lambda3.org/graphene/text#Parisian+caf%C3%A9s> .
_:394d55aacc064bcc82912689dc0500b9 <http://lambda3.org/graphene/extraction#predicate> <http://lambda3.org/graphene/text#were> .
_:394d55aacc064bcc82912689dc0500b9 <http://lambda3.org/graphene/extraction#object> <http://lambda3.org/graphene/text#centres+of+the+city+%27s+political+and+cultural+life> .
_:394d55aacc064bcc82912689dc0500b9 <http://lambda3.org/graphene/extraction#context-layer> "0"^^<http://www.w3.org/2001/XMLSchema#integer> .
<http://lambda3.org/graphene/text#Parisian+caf%C3%A9s> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "Parisian cafés"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://lambda3.org/graphene/text#were> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "were"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://lambda3.org/graphene/text#centres+of+the+city+%27s+political+and+cultural+life> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "centres of the city 's political and cultural life"^^<http://www.w3.org/2001/XMLSchema#string> .
_:394d55aacc064bcc82912689dc0500b9 <http://lambda3.org/graphene/extraction#VCON-TEMPORAL> <http://lambda3.org/graphene/text#by+the+18th+century+.> .
<http://lambda3.org/graphene/text#by+the+18th+century+.> <http://www.w3.org/1999/02/22-rdf-syntax-ns#value> "by the 18th century ."^^<http://www.w3.org/2001/XMLSchema#string> .
Full text extraction of the Barack Obama Wikipedia Page (2017-05-05):
The serialized class: JSON
The RDFNL format: RDFNL
The RDF N-Triples format: RDF
- Andre Freitas
- Bernhard Bermeitinger
- Christina Niklaus
- Leonardo Souza
- Matthias Cetto
- Siegfried Handschuh
- Java 8 (OpenJDK or Oracle)
- Maven 3.3.9
- Docker version 17.03+
- docker-compose version 1.12+
Compiling and packaging requires two additional packages:
cd /tmp
wget https://github.com/Lambda-3/SentenceSimplification/archive/v5.0.0.tar.gz -O SentenceSimplification.tar.gz
tar xfa SentenceSimplification.tar.gz
cd SentenceSimplification
mvn -DskipTests install
cd /tmp
wget https://github.com/Lambda-3/DiscourseSimplification/archive/v7.0.0.tar.gz -O DiscourseSimplification.tar.gz
tar xfa DiscourseSimplification.tar.gz
cd DiscourseSimplification
mvn -DskipTests install
More dependencies (requires docker)
Prior to running Graphene, two additional dependencies must be met:
Both are provided with the docker images:
Graphene-Core is build with
mvn clean package -DskipTests
If you want the server part, you have to specify that profile:
mvn -P server clean package -DskipTests
If you want the command line part, you have to specify that profile:
mvn -P cli clean package -DskipTests
To build both interfaces, you can specify both profiles:
mvn -P cli -P server clean package -DskipTests
Create a new config file and adjust your settings:
touch conf/graphene.conf
Then, you can build and start the composed images:
docker-compose up
Graphene comes with a Java API which is described here.
You must have a PyCobalt instance running, it is provided in the docker-compose-core.yml. Start it with docker-compose -f docker-compose-core.yml. You must then change the config file:
graphene {
coreference.url = "http://localhost:5128/resolve"
}
For simplified access, we wrapped the Graphene-Core library inside a REST-like web-service.
docker-compose upThe usage of the Graphene-Server is described here.
Another way of accessing our service is provided by a command-line interface, which is described here. Like the Graphene-Core setup, you must have a PyCobalt instance running before.