Computational Linguistics & Phonetics Computational Linguistics & Phonetics Fachrichtung 4.7 Universität des Saarlandes

Situation Entities project


Please cite the respective papers if you are using these resources. Thank you.

Annotation manual and other resources


  • MASC + Wikipedia texts annotated for situation entity types, genericity of main referent, habituality and lexical aspectual class (see LAW 2014, LAW 2015, ACL 2014, ACL 2015, EMNLP 2015, ACL 2016 papers) is available on GitHub (see annotated_corpus folder).
  • AspMASC.csv and AspAmbig.csv: data annotated for aspectual class (see ACL 2014 paper)
  • linguistic-indicators-Gigagword-AFE-XIE.csv: database of linguistic indicator values (see ACL 2014 paper) computed from Gigaword (AFE and XIE sections), extracted using the method described in: Siegel, E. V., & McKeown, K. R. (2000). Learning methods to combine linguistic indicators: Improving aspectual classification and revealing linguistic insights. Computational Linguistics, 26(4), 595-628.
  • WikiGenerics corpus v2.0: annotated for genericity on NP- and clause-level (see LAW 2015 and ACL 2015 papers) and clausal aspect (see EMNLP 2015 paper).


  • Implementation of systems described in ACL 2015 and ACL 2016 papers is available on GitHub (see de.uni-saarland.coli.sitent folder and pretrained_system for a simple version that you can just apply to your text).
  • Implementation of features for ACL 2015 paper is available from GitHub (including a simple-to-use command line tool).