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A tool to enrich any OCDM compliant Knowledge Graph, finding new identifiers and deduplicating entities

Project description

Tests Pyright Ruff Coverage REUSE status

OC GraphEnricher

OC GraphEnricher enriches OpenCitations Data Model (OCDM) compliant knowledge graphs by finding missing identifiers and deduplicating entities.

Documentation: https://opencitations.github.io/oc_graphenricher/

Quick start

pip install oc-graphenricher
from oc_ocdm.graph.graph_set import GraphSet
from oc_ocdm.reader import Reader
from rdflib import Graph

from oc_graphenricher.enricher import GraphEnricher
from oc_graphenricher.instancematching import InstanceMatching
from oc_graphenricher.storage import single_file_storage

graph = Graph().parse("data/input.nt", format="nt11")

reader = Reader()
graph_set = GraphSet(base_iri="https://w3id.org/oc/meta/")
reader.import_entities_from_graph(
    graph_set,
    graph,
    enable_validation=False,
    resp_agent="https://w3id.org/oc/meta/prov/pa/2",
)

GraphEnricher(
    g_set=graph_set,
    storage=single_file_storage(
        graph_path="enriched.json",
        provenance_path="provenance.json",
    ),
).enrich()
InstanceMatching(
    g_set=graph_set,
    storage=single_file_storage(
        graph_path="matched.json",
        provenance_path="provenance.json",
    ),
).match()

For configuration options and usage details, see the documentation.

License

Distributed under the ISC License. See LICENSE.

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