meaningslabel

Meaningslabel is a term used in semantic annotation to denote a tag that assigns the intended meaning of a word, phrase, or text span within a given context. It is employed in natural language processing, lexicography, and knowledge representation to support disambiguation when a surface form has multiple senses.

In practice, a meaningslabel corresponds to a category or identifier in a sense inventory or ontology. Annotators attach a single or multiple meaningslabels to tokens or spans, enabling systems to distinguish entre senses such as financial_institution versus river_bank. Labels can be hierarchical, allowing coarse-to-fine distinctions, and may be language-specific or mapped to cross-lingual inventories.

Meaningslabels are used in a variety of annotation schemes and data workflows. They can be derived manually, through crowdsourcing, or via automated alignment with dictionaries, thesauri, or knowledge graphs. They support downstream tasks by providing sense-aware representations for information retrieval, machine translation, question answering, and semantic search, among others.

Challenges associated with meaningslabels include selecting an appropriate sense inventory, achieving high inter-annotator agreement, and managing labeling costs. Cross-language and cross-domain consistency can be difficult, and overly rigid label schemas may obscure nuances of meaning in context.

Example: in the sentence “I went to the bank to withdraw money,” the token bank could be annotated with the meaningslabel financial_institution, whereas in “I sat on the river bank,” it could receive the label riverbank. See also word sense disambiguation, semantic annotation, sense inventory, and ontology.