{"categories":[{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic/2"}],"enrichment":{"capability":"Extracts entities, relations, and linguistic structures from text and documents using pretrained NLP models, then constructs knowledge graphs from the extracted information.","skillfed_tags":["nlp-extraction","knowledge-graph","entity-recognition"],"use_cases":["Extract named entities, terms, and linguistic structures from research papers or technical documents for downstream analysis.","Build knowledge graphs from patent or scientific literature collections to map relationships between concepts and entities.","Analyze document collections to identify and annotate domain-specific terminology and expressions at scale.","Convert unstructured text into structured, queryable linguistic annotations for information retrieval or semantic search.","Enrich PDF documents with NLP metadata (entities, relations, confidence scores) for indexing or downstream ML pipelines."],"what_it_does":"deepsearch-glm is a Python library for extracting structured linguistic information\u2014entities, relations, terms, and sentences\u2014from unstructured text and documents using pretrained neural language models. It processes raw text or JSON-converted documents to identify and annotate linguistic elements like named entities, expressions, and numeric values, then optionally constructs knowledge graphs from these extracted components across document collections.\n\nThe package provides two main workflows: direct NLP analysis on text snippets or full documents (returning pandas DataFrames with entity types, confidence scores, and character offsets), and graph construction from entity and relation annotations across multiple documents. It includes utilities for working with Deep Search document conversion and offers both Python bindings and C++ executables for batch processing.","worth_installing":"Yes, if you need entity and relation extraction from documents and are comfortable with a dormant package. The library offers broad Python version support and prebuilt wheels for easy installation, but the 613-day gap since the last release and lack of recent maintenance signals suggest limited ongoing support. Install only if the core NLP and graph-building features match your needs and you can tolerate potential staleness."},"id":"deepsearch-glm","links":{"html":"https://skillfed.io/packages/deepsearch-glm","md":"https://skillfed.io/packages/deepsearch-glm.md","pypi":"https://pypi.org/project/deepsearch-glm/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2024-12-09","license_spdx":null,"license_treatment":"permissive","name":"deepsearch-glm","python_support":"supports_current","summary":"Graph Language Models"},"popularity":{"monthly_downloads":92161,"position":13472,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.0"}