Narrative Schemas Database


A database of Narrative Schemas: structured sets of related events, semantic roles (the actors involved), and a temporal ordering of the events. See the publications below for details on the learning algorithm.

Since schemas are essentially clusters of verbs and their actors, schemas can be arbitrarily large. I am thus providing several different sizes of schemas for download. The clusters are grown until they reach the maximum size. While cutoff scores could be used to control cluster size, we are not convinced that this provides better schemas, and so are only cutting off at a specified size. However, we include each verb's score within its schemas so applications can make use of the scores for further tuning if they so choose.


Schemas Format

The format is a text file, not xml. It is easily readable by humans, but also structured for machine input. The following is an example schema with line by line descriptions.

Verb Order Format

The file contains pairwise counts of how often a pair of verbs was classified as before one another. The pair of verbs are listed in order. For instance, A B 23, indicates that A was classified as before B 23 times. B A 4 would indicate B before A (equally, A after B) 4 times. Each line is a tab-separated triple, the two verbs and the count.

See the publications below for details, but keep in mind that state-of-the-art temporal classification still has far to go. These counts come from supervised classifiers, so there are large chunks of unseen pairs with unreliable counts. When deciding if A is before B, you may want to compare the A B and B A counts to each other before making a decision.


This material is based upon work supported by the National Science Foundation under Grant No. IIS-0811974.


Unsupervised Learning of Narrative Schemas and their Participants
Nathanael Chambers and Dan Jurafsky
ACL-09, Singapore. 2009.

Unsupervised Learning of Narrative Event Chains
Nathanael Chambers and Dan Jurafsky
ACL-08, Ohio, USA. 2008.

Classifying Temporal Relations Between Events
Nathanael Chambers, Shan Wang, Dan Jurafsky
ACL-07, Prague. 2007. testing link