queryingtalen

Queryingtalen is a conceptual framework and accompanying toolkit designed to query multilingual language data using a unified, language-agnostic query language. It aims to let users express complex information needs that span multiple natural languages, linguistic annotations, and related metadata, drawing on ideas from cross-lingual information retrieval, semantic web technologies, and corpus linguistics.

Origin and development of the concept trace to discussions in computational linguistics during the late 2010s and early 2020s, when researchers sought methods to access diverse multilingual resources without duplicating queries for each language. The framework borrows from data models such as RDF and query languages like SPARQL and SQL, adapting them to linguistic data and annotations.

Core concepts include an abstract representation of linguistic units (such as words, lemmas, annotations, and alignments) and a set of operators for filtering, projecting, joining, and aggregating across languages. Queryingtalen emphasizes modular adapters that connect to various data stores, including parallel corpora, lexical databases, and annotated corpora, enabling hierarchical and nested analyses.

Syntax and semantics are designed to be expressive yet compositional. The syntax resembles a hybrid of functional and declarative styles, with keywords for select, where, join, and map, plus language qualifiers to constrain results by language code. Semantics are defined so that the meaning of a composite query follows from the meanings of its parts.

Applications include cross-lingual search, multilingual lexicography, documentation of endangered languages, and digital humanities projects. The framework is discussed as a research platform for evaluating multilingual NLP models and workflows, while challenges persist in data heterogeneity, standardization, scalability, and ethical considerations around language data.