Discovery Procedure for ERG Semantic Phenomena

We developed a discovery procedure which starts from grammar entities (phrase structure rules, lexical rules, and lexical types) in the current version of the ERG to enable a data-driven exploration of semantic phenomena which have received treatments in the ERG to date. The discovery procedure starts by identifying grammar entities which are likely to contribute to the composition of semantic representations that go beyond the basics. In the case of phrase structure rules and lexical rules, we identified all instances with non-empty C-CONT.RELS values. In the case of lexical types, we found all those which exhibit at least one of the following properties:

  • More than one EP in CONT.RELS
  • At least one of the EPs in CONT.RELS has at least one scopal argument

We plan to also look for (classes of) lexical entries with CARGs and grammar predicates (suggesting lexical decomposition), but this has yet to happen. Each extracted grammar entity is associated with a signature, for now just the (multi-)set of PRED values in the EPs in its RELS list.

We then took the grammar entities and created rough clusters based on shared signatures, clustering only within broad grammar entity class (phrase structure rules, lexical rules, or lexical types). While it might be more informative to extend the sets of EPs to a more proper semantic signature, this was not done in the first pass.

Once the grammar entities and clusters were extracted, we indexed the existing collection of Redwoods treebanks (including DeepBank) for all grammar entity types. This enabled us to extract examples for each grammar entity of interest. These lists of examples include the three shortest available across the Redwoods corpora, plus all examples from the MRS test suite. Working from the phrase structure and lexical rule clusters and their associated examples, we produced an initial set of proposed phenomena to document (listed on the inventory page). Among the phenomena, we found a few types of information in the MRS which we believe to be MRS-based encodings of quasi-semantic or para-semantic phenomena. These are listed separately.

This procedure seems to have been effective for the rules, but less so for the lexical types. We looked some at the clusters and examples for lexical types, and from there were able to extract a non-exhaustive list of phenomena as well as a candidate set of basic components of semantic analyses which should be documented. These, too, are noted on the inventory page.

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Last update: 2014-11-04 by StephanOepen [edit]