# Computational Linguistics **Domain:** Linguistics / Computer Science / Artificial Intelligence **Doc Type:** Canonical Discipline Node **Maturity:** Developed **Related:** [[wiki/Natural Language Processing|Natural Language Processing]], [[wiki/Language|Language]], [[wiki/Knowledge Representation|Knowledge Representation]], [[wiki/Corpus Engineering|Corpus Engineering]], [[wiki/Formal Grammar|Formal Grammar]] --- ## Definition **Computational linguistics studies how linguistic structure can be represented, analyzed and generated computationally.** It joins formal accounts of sound, grammar and meaning with algorithms, corpora and software systems. The field overlaps with [[wiki/Natural Language Processing|Natural Language Processing]] but is not identical to it. NLP is commonly organized around working capabilities such as translation, retrieval, classification and generation. Computational linguistics also asks what representations of phonology, syntax, semantics and discourse make those capabilities possible and what the resulting systems reveal about language. ## Symbolic Language Engine Context [[projects/Ten Years Building a Symbolic Language Engine|Ten Years Building a Symbolic Language Engine]] is a computational-linguistics project because it makes several layers of English separately addressable: pronunciation, rhyme, syllable structure, lexical sense, taxonomic relation, corpus association and poetic form. Its central engineering question is not merely how to return an answer, but which representation makes a linguistic question cheap to ask. The project also crosses historical paradigms. Explicit phonological and semantic structures belong to the symbolic tradition; trigger relations and corpus frequencies belong to statistical language modeling; a modern reconstruction would add embeddings and neural models while retaining source-specific explanations. ## Key Insight **Language becomes computationally useful when its different structures can be represented without pretending they are all the same kind of relation.** ## See Also [[wiki/Natural Language Processing|Natural Language Processing]], [[wiki/Symbolic Language Engine|Symbolic Language Engine]], [[wiki/Lexical Semantics|Lexical Semantics]], [[wiki/Phonological Representation|Phonological Representation]], [[wiki/Distributional Semantics|Distributional Semantics]], [[wiki/Provenance-Sensitive Multiplicity|Provenance-Sensitive Multiplicity]] ## Sources / Provenance - Christopher Manning and Hinrich Schütze, *Foundations of Statistical Natural Language Processing* (1999). - Daniel Jurafsky and James H. Martin, *Speech and Language Processing*.