computational-linguistics

## What I do - Apply linguistic theory to computation - Build language models with linguistic structure - Implement syntactic and semantic analysis - Create cross-linguistic NLP systems - Handle multilingual text processing ## When to use me Use me when: - Building linguistically-aware NLP - Multilingual applications - Grammar and syntax processing - Semantic representation ## Key Concepts ### Linguistic Analysis Levels ``` ┌─────────────────────────────────────────────┐ │ Discourse │ │ (context, coherence) │ ├─────────────────────────────────────────────┤ │ Semantics │ │ (meaning, representation) │ ├─────────────────────────────────────────────┤ │ Pragmatics │ │ (intent, context, speech acts) │ ├─────────────────────────────────────────────┤ │ Syntax │ │ (grammar, structure rules) │ ├─────────────────────────────────────────────┤ │ Morphology │ │ (word formation, inflections) │ ├─────────────────────────────────────────────┤ │ Phonology/Orthography │ │ (sounds, written form) │ └─────────────────────────────────────────────┘ ``` ### Syntax Parsing ```python import spacy nlp = spacy.load("en_core_web_sm") doc = nlp("The cat sat on the mat.") # Part-of-speech tags for token in doc: print(token.text, token.pos_, token.tag_) # Dependency parsing for token in doc: print(token.text, token.dep_, token.head.text) # Named entities for ent in doc.ents: print(ent.text, ent.label_) ``` ### Semantic Representation - **Formal Semantics**: Lambda calculus, FOL - **Frame Semantics**: FrameNet - **Semantic Primitives**: Primitive theory - **Distributional Semantics**: Word embeddings ### Linguistic Resources - **WordNet**: Lexical database - **UD**: Universal Dependencies - **Penn Treebank**: Syntactic annotations - **BabelNet**: Multilingual lexical knowledge