This summer–out of town, meeting many new people–I encountered far more often the unenviable dilemma of explaining my dissertation topic. Unintentionally, though, I turned it into an experiment.
Linguistics: where talking about an experiment becomes another experiment.
Typically, when introducing the topic, I presented a set of verbs, “arrest, search, apprehend, try, convict” and asked what nouns came to mind. Most folks drew a blank. At first I thought it was a fluke, but after a sustained near-0% success rate, and failing so frequently to explain to so many people what I was doing, I got my head out of my ass and admitted that I was explaining wrong.
So instead of giving them verbs and asking what nouns came to mind, I gave them “police and suspect” and asked them what words come to mind. “arrest, search…” It worked like a charm.
It’s easy to think of the actors and the actions associated with them as interchangeable, and then to emphasize the extracted product of the process (Chambers and Jurafsky 2009). After all, that list of verbs is a project result. However, coreference chains–strings of co-referring nouns–are employed at the first step, so it’s more sensible to convey the process nouns-first. Then, in a way, the listener becomes the project, and that’s way more interesting for them and you.
Furthermore, this may signal a need to alter the schema construction process. Verbs are compared to one another, and though their similarity depends on their co-referrent arguments, the choice of comparison depends on grammatical/referent collocations of verbs, not the juxtaposition of two actors. In this direction, the pair of actors I prompted listeners with is similar to those in Balasubramanian et al. 2013, retaining a pairwise relationship between role fillers through the extraction process.
In the end, it’s the nouns I’m interested in. On my 2nd Qualifying Paper, I looked at narratives related to police. Fundamentally, I was interested in what the system told me about police and how they interacted with other argument types: suspects, bystanders, etc. A noun-centric generation process may provide results more suited to this sort of analysis.
A noun-centric process may also improve performance in more challenging domains. I noticed analyzing movie reviews that, while the means of describing films and reviewer sentiment about them varied, particular roles remained constant throughout the domain: the reviewer, the director, characters in a plot synopsis, the film itself. Since that’s where I’m headed, that seems to be the way to think about things.