This is the repository for the Argument Structure Construction (ASC) Treebank. The ASC Treebank was used to train a Spacy transformer model that annotates ASCs with a high degree of accuracy (F1 = .918).
Learned correspondences between form and function vary in terms of complexity and abstractionm, and so do the examples of the ASCs. There is currently no definitive set of ASCs that should be included in an ASC tagset. The current study drew on a range of previous literature and selected nine ASC types as a tagset.
| ASC tag | Syntactic frame (example) | Semantic frame (example) |
|---|---|---|
| ATTR | Subj-Vcopular-NP | Xtheme is Yattribute |
| INTRAN_S | Subj-V | Xagent acts |
| INTRAN_MOT | Subj-V-Adverbial Particle/PP | Xtheme moves Ypath |
| INTRAN_RES | Subj-V-NP/AdjP | Xpatient becomes Yresult |
| TRAN_S | Subj-V-Obj | Xagent acts on Ypatient |
| DITRAN | Subj-V-Objindirect-Objdirect | Xagent causes Yrecipient to receive Ztheme |
| CAUS_MOT | Subj-V-Obj-PP | Xagent causes Ytheme to move Zpath/goal |
| TRAN_RES | Subj-V-Obj-NP | Xagent causes Ytheme to become Zstate |
| PASSIVE | Subj-auxVpast participle(-by-PP) | Xtheme undergo V (by Yagent) |
The documenation for the ASC-Treebank is available here.
The annotation model (including a demo) is available here.
If you use the model or the treebank, please cite this paper:
Kyle, K. & Sung, H. (2023). An argument structure construction treebank, In Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023), 51–62, Association for Computational Linguistics.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
