Software developed by the NLP lab is available below. If you have any questions, please contact Prof. Di Eugenio at This e-mail address is being protected from spambots. You need JavaScript enabled to view it .



Intelligent Tutoring systems for introductory Computer Science. Please see


The NLP lab is pleased to release the following corpora. If interested in obtaining them, please contact Prof. Di Eugenio at This e-mail address is being protected from spambots. You need JavaScript enabled to view it .


Instructional corpus annotated with Rhetorical Relations.

This  is  a 5MB  corpus on home-repair composed of 176 documents containing written English instructions. Texts were  manually segmented into Elementary Discourse Units (EDUs). The corpus contains an average of 32.6 EDUs per document, for a total of 5744 EDUs and 53,250 words. Further, the corpus was manually annotated for 5172 rhetorical relations in the RST tradition (please see some pointers below). The corpus was originally developed under NSF Award IIS-0133123, and is further described in the following paper

Rajen Subba and Barbara Di Eugenio. An effective Discourse Parser that uses Rich Linguistic Information. NAACL-HLT 2009. The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics. Boulder, Co. June 2009.

Some pointers to RST: [Mann & Thompson 88], in Text-Interdisciplinary Journal for the Study of Discourse, 8(3);  [Moser and Moore 96] in Computational Linguistics 22(3), [Marcu 99], in ACL 1999.


It contains 19 transcribed dialogues between two subjects (a helper and an elderly person) performing Activities of Daily Living (walking, preparing dinner, getting up from a chair) in a realistic environment. The interactions were videotaped, and both subjects wore a microphone, and a data glove  to collect haptic data. The 19 dialogues in this corpus were transcribed in their entirety and then they were coded with multimodal annotations. Annotations include: co-reference, dialogue acts and dialogue games; pointing gestures; haptic-ostensive actions, and haptic interactions. Within the 19 dialogues, most types of annotations have been performed on 137 "Find tasks" (about 30% of the transcribed data: 1516 utterances, 6593 words, almost 1000 pointing gestures + haptic actions). A FindTask is a continuous time span during which the two subjects are collaborating on finding and retrieving objects that are needed to perform Activities of Daily Livings such as preparing dinner. The data has been annotated with Anvil

The released corpus only contains the transcribed dialogues + their annotations (we regret that we cannot release the original videos due to human subject protection constraints; as concerns the haptic data we collected, it is not included per se in this release, but the annotation is).

The RoboHelper/FindTask was collected under NSF Award IIS-0905593. Further details can be found in the following paper:

Lin Chen, Maria Javaid, Barbara Di Eugenio, Miloš Žefran, "The roles and recognition of Haptic-Ostensive actions in collaborative multimodal human–human dialogues", Computer Speech & Language, Volume 34, Issue 1, November 2015, Pages 201-231.