Overview
ISO 24617-15:2025, part of the ISO 24617 series on language resource management, introduces a standardized framework for measurable quantitative information extraction (MQIE). Developed by the International Organization for Standardization (ISO), this standard provides guidance for extracting, normalizing, and structuring quantitative data-such as measurements, durations, and spatial measures-from natural language texts. Building on the semantic annotation principles defined in ISO 24617-11, this part is focused on the technological and applicational aspects of extracting quantitative information, distinguishing itself from more theoretical standards.
The MQIE scheme is highly relevant for application areas where precise quantitative information is crucial, including scientific, medical, technical, and business domains. It ensures interoperability across varied quantitative data types, including temporal durations and spatial measures, and supports integration with other semantic frameworks within the ISO 24617 series.
Key Topics
- Measurable Quantitative Information (MQI): Information in text that combines a numerical value and a unit, essential for expressing data such as dimensions, quantities, or measures.
- Extraction Strategies:
- Manual, semi-automated, automated, and hybrid approaches are included.
- Automated methods include rule-based, machine learning, and deep learning approaches.
- Framework Steps:
- Preprocessing: Cleans and standardizes the text to remove noise and inconsistencies.
- Element Identification: Detects entities, numerals, units, and relational terms (relators).
- Link Identification: Establishes measure links (connecting quantities to entities) and comparison links (comparing values).
- Measure Normalization: Converts all extracted measures into consistent, comparable units and values.
- Verification and Filtering: Applies domain knowledge and rule-based validation to ensure extraction quality.
- Interoperability: Accommodates integration with other measure types, such as temporal and spatial measures, as specified in related ISO standards.
Applications
The MQIE framework defined in ISO 24617-15:2025 is designed to support a broad array of practical uses:
- Healthcare and Clinical Research: Enables automated extraction of lab results, dosages, and eligibility criteria from electronic medical records, aiding in data analysis and patient management.
- Scientific Publishing: Supports efficient information retrieval and knowledge management by structuring experimental results, measurements, and data points from scientific papers.
- Business Analytics and Financial Reporting: Assists in aggregating and analyzing key financial metrics-such as sales figures, revenues, and expenses-from annual reports and financial documents.
- Technical Documentation: Extracts specifications, measurements, and capacities from manuals and product reports for easier indexing and retrieval.
- Natural Language Processing (NLP): Provides standardized annotations for measurable information, improving tasks like question answering, text summarization, and information retrieval in large text corpora.
The inclusion of examples and validation steps ensures that extracted quantitative information is accurate, contextually relevant, and ready for downstream computation or analysis.
Related Standards
ISO 24617-15:2025 is interconnected with several key standards in the field of semantic annotation and language resource management:
- ISO 24617-11 (SemAF-MQI): Defines the semantic annotation schema for measurable quantitative information; the foundation for MQIE.
- ISO 24617-1 (Temporal Durations): Addresses the representation of temporal information and durations, integrated within MQIE when dealing with time-based measures.
- ISO 24617-6 (SemAF Principles): Provides the overarching principles for semantic annotation frameworks.
- ISO 24617-7 (Spatial Measures): Focuses on the annotation of spatial measurements and distances, which are interoperable within MQIE.
- ISO 24617-12: Covers broader theoretical issues related to quantification and quantitative information.
These standards, together with ISO 24617-15:2025, promote consistency, interoperability, and reliability in the extraction, normalization, and application of quantitative data from diverse text sources. Adopting the MQIE framework helps organizations and developers meet the growing demands for robust, automated quantitative information extraction in modern data-driven environments.
Open preview (PDF)Language resource management — Semantic annotation framework (SemAF) — Part 15: Measurable quantitative information extraction (MQIE)