Members of the Stanford NLP Group pursue research in a broad variety of topics:

Computational Semantics

• Extraction of meaning representations from text, ranging from shallow representations like named entities and thematic roles, to deep structures like quantification in logic. Research topics include:

  • Natural Logic and Inference
  • Narratives and Event Representations
  • Mimir Project: Topic Modeling over Time
  • Detecting Contradictions in Text
  • Semantic Taxonomy Induction
  • Named Entity Recognition (NER) and Information Extraction (IE)
    • The Stanford Edinburgh Entity Recognition (SEER) Project
    • The Edinburgh And Stanford Information Extraction (EASIE) Project
  • Shallow Semantic Parsing
  • Question Answering (QA)
  • Knowledge Representation from Text
    • The NLKR Project: solving natural-language logic puzzles
  • Word Sense Disambiguation (WSD)

Parsing & Tagging

• Algorithms for assigning part of speech and syntactic structure, emphasizing probabilistic and discriminative models. Research topics include:

  • Probabilistic Parsing
  • Part-of-speech (POS) tagging

Machine Translation

• Language modeling, re-ordering models, phrase extraction techniques, syntactic methods, and better training for statistical machine translation:

  • Machine Translation

Multilingual NLP

• A variety of NLP investigations in Chinese, Arabic, and German, including tagging, segmentation, probabilistic syntactic parsing, and semantic role parsing, as well as work on speech processing. Research topics include:

  • Chinese NLP and Speech
  • Arabic NLP
  • German NLP

Unsupervised Induction of Linguistic Structure

• Probabilistic and other corpus-based algorithms for learning syntactic, morphological, and phonological structures from corpora. Research topics include:

  • Grammar Induction
  • Morphology & Phonology Induction
  • Semantic Taxonomy Induction

Other

• A number of other research areas in the computational study of human language. Research topics include:

  • Personalized PageRank algorithms
  • Clustering Models
  • Computational Lexicography: Kirrkirr
  • Text Categorization
  • Discriminative Models

Links

Other groups at Stanford doing NLP-related research:

Other links: