e5a532a8bc
- Introduced `test_nlp_extractor.py` with unit tests for the InstitutionExtractor, covering various extraction patterns (ISIL, Wikidata, VIAF, city names) and ensuring proper classification of institutions (museum, library, archive). - Added tests for extracted entities and result handling to validate the extraction process. - Created `test_partnership_rdf_integration.py` to validate the end-to-end process of extracting partnerships from a conversation and exporting them to RDF format. - Implemented tests for temporal properties in partnerships and ensured compliance with W3C Organization Ontology patterns. - Verified that extracted partnerships are correctly linked with PROV-O provenance metadata.
21 lines
670 B
Python
21 lines
670 B
Python
"""
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GLAM Extractor
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A comprehensive toolkit for extracting and standardizing global GLAM (Galleries,
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Libraries, Archives, Museums) institutional data from conversation transcripts and
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authoritative registries.
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"""
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__version__ = "0.1.0"
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__author__ = "GLAM Data Extraction Project"
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# TODO: Import actual implementations when ready
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# from glam_extractor.parsers import ConversationParser, CSVParser
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# from glam_extractor.extractors import InstitutionExtractor, IdentifierExtractor
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# from glam_extractor.validators import LinkMLValidator
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# from glam_extractor.exporters import JSONLDExporter, RDFExporter, CSVExporter
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__all__ = [
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"__version__",
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"__author__",
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]
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