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OntologyService

What it is​

  • A thin service wrapper that exposes Named Entity Recognition (NER) against a provided ontology string.
  • Delegates the actual NER work to an injected IOntologyNERPort adaptor and returns an rdflib.Graph.

Public API​

  • class OntologyService(IOntologyService)
    • __init__(ner_adaptor: IOntologyNERPort, ontology_str: str)
      • Stores the NER adaptor and the ontology data (as a string) used for recognition.
    • named_entity_recognition(input: str) -> rdflib.Graph
      • Runs NER on input using the stored ontology string by delegating to the adaptor:
        • ner_adaptor.named_entity_recognition(input, ontology_str)

Configuration/Dependencies​

  • Depends on:
    • naas_abi_core.services.ontology.OntologyPorts.IOntologyNERPort (injected adaptor)
    • naas_abi_core.services.ontology.OntologyPorts.IOntologyService (service interface)
    • rdflib.Graph (return type)

Usage​

from rdflib import Graph
from naas_abi_core.services.ontology.OntologyService import OntologyService

# Minimal stub adaptor matching the expected port method signature
class DummyNERAdaptor:
    def named_entity_recognition(self, text: str, ontology_str: str) -> Graph:
        return Graph()  # replace with real extraction logic

ontology_str = "<your ontology as a string>"
service = OntologyService(ner_adaptor=DummyNERAdaptor(), ontology_str=ontology_str)

g = service.named_entity_recognition("Some input text")
print(type(g))  # <class 'rdflib.graph.Graph'>

Caveats​

  • No validation is performed:
    • ontology_str is passed through as-is to the adaptor.
    • The returned Graph content and semantics depend entirely on the adaptor implementation.