Versions Edit

Version 1.0 (AKA version II) Edit

Main reference: Baker & Sato (2003)[1]

No fulltext corpus.

Version 1.3 Edit

From Baker et al. (2007)[2] "The current release (1.3) of the FrameNet data, which has been freely available for instructional and research purposes since the fall of 2006, includes roughly 780 frames with roughly 10,000 word senses (lexical units). It also contains roughly 150,000 annotation sets, of which 139,000 are lexicographic examples, with each sentence annotated for a single predicator. The remainder are from full-text annotation in which each sentence is annotated for all predicators; 1,700 sentences are annotated in the full-text portion of the database, accounting for roughly 11,700 annotation sets, or 6.8 predicators (=annotation sets) per sentence. Nearly all of the frames are connected into a single graph by frame-to-frame relations, almost all of which have associated FE-to-FE relations (Fillmore et al., 2004a) 2.1"

Criticisms Edit

The main problem with FrameNet as a formalization is that it is too specific. Whenever people move into a new genre, they will find themselves defining new frames and of course systems trained on newswire-oriented FrameNet corpus will have no chance getting them. For example:

  • Coppola et al. (2009)[3] worked on call centre data and defined "20 new ad hoc frames specific for the domain. New frames mostly con- cern data processing such as NAVIGATION, DIS- PLAY DATA, LOSE DATA, CREATE DATA."
  • Ruppenhofer et al. (2010)[4] worked with Sherlock Holmes excerpt and "encountered many new frames and lexical units for which we could not ourselves create the necessary frames and provide lexicographic annotations."

References Edit

  1. Baker, C. F., & Sato, H. (2003, July). The FrameNet data and software. In Proceedings of the 41st Annual Meeting on Association for Computational Linguistics-Volume 2 (pp. 161-164). Association for Computational Linguistics.
  2. Baker, C., Ellsworth, M., & Erk, K. (2007). SemEval-2007 Task 19: Frame Semantic Structure Extraction. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007) (pp. 99–104). Association for Computational Linguistics.
  3. Coppola, B., Moschitti, A., & Riccardi, G. (2009). Shallow Semantic Parsing for Spoken Language Understanding. Proceedings of NAACL HLT, (June), 85–88.
  4. Ruppenhofer, J., Sporleder, C., Morante, R., Baker, C., & Palmer, M. (2010). SemEval-2010 Task 10: Linking Events and Their Participants in Discourse. In Proceedings of the 5th International Workshop on Semantic Evaluation, ACL 2010 (pp. 45–50). Uppsala, Sweden.