Adina Williams


You can view my CV here (updated 11/08/17).

I am PhD candidate in Linguistics at New York University.  I specialize in semantics, syntax, and their interface, using psycholinguistics, neurolinguistics, and computational linguistics as my main methodologies. I foreground theoretical linguistic insights as the basis for hypotheses about grammatical representations in the mind and computer. I work in the NYU Neuroscience of Language Lab (NELLab) with Liina Pylkkänen on the neural bases of the semantic processing of argument structure, and in the  ML² Group with Sam Bowman.  

I recently released the Multi-genre Natural Language Inference (MultiNLI) corpus (summer 2017). This corpus is a crowd-sourced collection of sentence pairs (433k) annotated with textual entailment information for use in NLP and Machine Learning applications. It was the basis of shared task associated with the RepEval 2017 Workshop at EMNLP 2017 (Copenhagen). The manuscript describing the data and giving some baselines is available here; a manuscript detailing the results of the shared task is available here. We thus far used MultiNLI as part of some exciting new work on evaluating latent parse trees that were arrived at by end-to-end deep architectures doing Natural Language Inference without reference to explicit parse trees at training (see arxiv here).

When not looking at pretty brains or coding, I do theoretical work on the syntax-semantics interface at the overlap of the Semantics Group, the Syntax Research Group, and the Morphology Reading Group, where I work on the semantics of inflectional morphology (mainly viewpoint aspect and its connection to adpositional meaning in Mandarin Chinese, and number and definiteness in American English), and investigate the effect of lexical “constants” on syntactic realization.  


Brief Summary of Interests


  • Syntax-Semantics Interface
  • Experimental & Computational Approaches to Linguistics


  • Brain Basis of Syntactic and Semantic Processing
    • Argument Structure and Event Structure
    • Syntactic Category
    • Representations of Number
  • Natural Language Understanding 
    • How NLP methods can aid in the investigation of meaning
    • Creating Corpora for Natural Language Inference
    • Evaluating syntactic representations induced from TreeRNNs that do semantic tasks
  • Semantics of Inflectional Morphology
    • Number Interpretation, Marking, and Countability
    • Prepositional and Verbal Aspect
    • Bare Singulars and Weak Definites
  • (Morpho)Syntax and Semantics of Mandarin Chinese