Spring ’18, M 10:00–12:00, Denny Hall 265
Instructor: Michael White
Advances in Computational Semantics
This course will first cover introductory topics related to semantic construction and interpretation from the novel perspective of a Haskell implementation of dynamic continuized combinatory categorial grammar (dyc3g), a theoretically motivated approach to compositional dynamic semantics with attractive computational properties. Subsequently, the course will pursue a selection of advanced topics through readings and course projects. No prior knowledge of Haskell or dyc3g will be required.
Advanced topics may include:
- implementing grammar fragments in dyc3g that explore linguistic phenomena such as quantification with plurals, incremental quantification and pair-list phenomena, binding and anaphora, focus-sensitive operators or prosody, negative polarity items, and definite descriptions of the rabbits-in-hats variety;
- empirical work looking at analyses of sentences in the GeoQuery corpus in comparison to those derived with the Cornell/UW semantic parsing framework, and possibly training statistical parsers for dyc3g on this corpus; and
- combining distributional and compositional semantics for inference and textual entailment.
Students are encouraged to pursue related research interests for their term project. Topics will be finalized based on the interests of the participants.
Students will be expected to actively participate in the discussion and research carried out in the seminar. As detailed below, students will be required to complete the introductory exercises, facilitate discussions and post questions on the readings in advance, as well as locate relevant background/tutorial materials. Additionally, students taking the course for 3 credits will be required to carry out a class project on a topic related to the seminar; alternatively, for students already working on a related topic, integrating their focus into the seminar will be an option.
Ling 5801 or equivalent, or permission of the instructor.
We’ll use Carmen to manage the exercises, schedule discussion facilitators and post advance questions on the readings, as well as links to background/tutorial materials. We’ll also use it for submitting project documents.
Basic exercises covering the introductory material will be reviewed in class on the due data. Exercises will be graded on a simple completion basis. Collaborative work on the exercises is encouraged but each student should turn in his or her own programs and write-ups, which should mention whether and with whom the work was done collaboratively.
Exercises may also include cooperative data analysis, for example analyzing CCG parsing errors on the GeoQuery corpus.
Class participation (15%)
We are aiming for a dynamic discussion of papers, not death by powerpoint. Thus, we plan on taking a page from Eric Fosler-Lussier’s playbook and requiring everyone (this includes you!) to post at least one question to the discussion list on Carmen, ideally by 8 p.m. the Friday before each week’s readings will be discussed. Participants should also feel free to share their (initial) thoughts and views of the papers in their posts. In particular, questions of the type “What did they mean by X” or “Why did they do X instead of Y” are encouraged. Remember that most of the papers are targeted to people who are already expert in the area, so you shouldn’t expect to alway understand everything. Airing such questions can help everyone gain a better understanding of the paper — even those who thought they understood it!
Facilitating discussions (15%)
Each week’s meeting will have a discussion facilitator. For the main readings, the facilitator should look over the posted questions and choose a subset for discussion. In class, the facilitator should start the session with a brief, five to ten minute summary of the papers, including the highlights and lowlights. Following the opening summary, the facilitator is responsible for managing the discussion, and ensuring that as many viewpoints are heard as possible.
Students will be required to facilitate at least one session during the course. If the discussion does not take up the entire class period, the remaining time may be used to (informally) discuss class projects.
Term project (50%)
As noted above, students taking the course for 3 credits will be required to carry out a term project, either alone or in a team setting. A project sketch will be required to be presented informally in class for brainstorming during the tenth week, followed by a presentation during the last week of class, and a final report by the day the final exam would be held (if there were one).
For students taking the course for 1 credit, no project will be required, with the other requirements scaled accordingly.
The topics and readings we expect to cover are listed below; these will be refined as the course progresses.
Semantic Parsing with CCG
- Luke Zettlemoyer and Michael Collins. 2005. Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars. In Proceedings of the Twenty First Conference on Uncertainty in Artificial Intelligence (UAI-05).
- Luke Zettlemoyer and Michael Collins. 2009. Learning Context-Dependent Mappings from Sentences to Logical Form. In Proceedings of ACL 2009, pp. 976–984.
- Tom Kwiatkowski, Luke Zettlemoyer, Sharon Goldwater and Mark Steedman. 2010. Inducing Probabilistic CCG Grammars from Logical Form with Higher-Order Unification. In Proceedings of EMNLP 2010.
- Tom Kwiatkowski, Luke Zettlemoyer, Sharon Goldwater and Mark Steedman. 2011. Lexical Generalization in CCG Grammar Induction for Semantic Parsing. In Proceedings of EMNLP 2011.
- Tom Kwiatkowski, Eunsol Choi, Yoav Artzi, and Luke Zettlemoyer. 2013. Scaling Semantic Parsers with On-the-fly Ontology Matching. In Proceedings of EMNLP 2013.
- Yoav Artzi and Luke Zettlemoyer. 2013. Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions. Transactions of the Association for Computational Linguistics, 1, 49–62.
Continuized Grammars and (Monadic) Dynamic Semantics
- Chris Barker. 2002. Continuations and the nature of quantification. Natural Language Semantics, 10:211–242.
- Chris Barker and Chung-chieh Shan. 2015. Continuations and Natural Language. Oxford University Press.
- Simon Charlow. 2014. On the semantics of exceptional scope. Doctoral dissertation, New York University.
- Dylan Bumford. 2017. Split-scope definites: Relative superlatives and Haddock descriptions. Linguistics and Philosophy, 40(6):549–593.
- Michael White, Simon Charlow, Jordan Needle and Dylan Bumford. 2017. Parsing with Dynamic Continuized CCG. In Proc. of the 13th International Workshop on Tree-Adjoining Grammar and Related Formalisms (TAG+13). (bib) (slides)
- Chung-chieh Shan. 2004. Polarity sensitivity and evaluation order in type-logical grammar. In Proc. of NAACL-04.
- Chris Barker and Chung-chieh Shan. 2006. Types as graphs: continuations in Type Logical Grammar. Journal of Logic, Language and Information 15,
- Adrian Brasoveanu. 2007. Structured Anaphora to Quantifier Domains:
A Unified Account of Quantificational and Modal Subordination. In Proc. of the 14th Workshop on Logic, Language, Information and Computation.
Distributional Semantics and Composition
- Mike Lewis and Mark Steedman. 2013. Combined Distributional and Logical Semantics. Transactions of the Association for Computational Linguistics, 1:179–192.
- Mark Steedman and Jason Baldridge. 2011. Combinatory Categorial Grammar (a tutorial introduction), pre-print. In R. Borsley and K. Borjars (eds.), Non-Transformational Syntax, Wiley-Blackwell.
- NASSLLI (2012) Course on CCG for NLP
- Julia Hockenmaier and Mark Steedman. 2007. CCGbank: A Corpus of CCG Derivations and Dependency Structures Extracted from the Penn Treebank, Computational Linguistics, 33:3, 355–396.
- Matthew Honnibal, James R. Curran and Johan Bos. 2010. Rebanking CCGbank for improved NP interpretation. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics.
- Semantic Parsing ACL Tutorial (2013)
- Cornell Semantic Parsing Framework
- Haskell Platform
- FP Complete’s School of Haskell
- Real World Haskell (O’Reilly)
- Learn You a Haskell for Great Good! (the funkiest)
- The Haskell Wikibook
- Philip Wadler. 1995. Monads for functional programming.
- Chris Barker and Dylan Bumford. 2015. Monads and Natural Language, ESSLLI Barcelona.
Policy on Academic Misconduct
As with any class at this university, students are required to follow the Ohio State Code of Student Conduct. In particular, note that students are not allowed to, among other things, submit plagiarized (copied but unacknowledged) work for credit. If any violation occurs, the instructor is required to report the violation to the Council on Academic Misconduct.
Students with Disabilities
Students who need an accommodation based on the impact of a disability should contact me to arrange an appointment as soon as possible to discuss the course format, to anticipate needs, and to explore potential accommodations. I rely on the Office of Disability Services for assistance in verifying the need for accommodations and developing accommodation strategies. Students who have not previously contacted the Office for Disability Services are encouraged to do so (292-3307; http://www.ods.ohio-state.edu).
This syllabus is subject to change. All important changes will be made in
writing (email), with ample time for adjustment.