📅 2024-09-12 — Session: Developed and Enhanced Spanish NLP Parser
🕒 00:15–01:05
🏷️ Labels: NLP, Spacy, Spanish, Parser, Entity Extraction
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal: The session aimed to develop and enhance a natural language processing (NLP) parser for Spanish sentences, focusing on entity extraction and dependency analysis.
Key Activities:
- Installed the Spanish language model (
es_core_news_sm) in spaCy to facilitate sentence processing. - Analyzed sentence structures, focusing on syntactic components and dependencies, particularly in healthcare contexts.
- Developed a parser to identify and group key sentence components such as actions, subjects, locations, and institutions.
- Updated parser logic to improve accuracy in entity extraction, using dependency parsing and named entity recognition (NER).
Achievements:
- Successfully installed and utilized the Spanish language model in spaCy.
- Enhanced the parser’s capability to accurately extract and group entities in Spanish sentences, particularly in complex structures.
Pending Tasks:
- Further refine the parser to handle more complex sentence structures and improve entity recognition accuracy.
- Test the parser in diverse contexts to ensure robustness and adaptability.