gusl: (Default)
My argumentative structures project has been kinda stuck. I can't think of anything interesting to do with the data I have.

Today I spoke to Wilfried Sieg, who said that the project of doing machine learning on inferences in logic textbooks (tagged with inference type) would be interesting to him, even if it isn't interesting to William. For one thing, this could provide automatic grading for logic courses.

Journals that would be interested in such work:
* Teaching Philosophy
* NA-CAP (this year in Chicago, proposals due March 21)

I don't find this task terribly interesting, but maybe it could open the ground for more interesting things, as we slowly make progress towards modeling arguments in real-world texts. I should look for prior work. But it's still unclear how learning on logic textbooks could transfer enough to get us reasonable performance on real-world texts. Do we even have intermediate corpora between formalistic logic textbooks and real-world argumentative texts, with which to guide this learning?
gusl: (Default)
One of my projects is about annotating the argumentative structure of texts.

My advisor is interested in sources like newspaper editorials, political blogs, etc. He likes to annotate expressions of agreement/disagreement, sentiment, etc. He's not interested in formalizing "normative arguments", such as those found in math/science textbooks or philosophy texts, let alone something formalistic like Landau's Grundlagen (Automath version + full text in LaTeX, simple type theory version 1 2), because we have no reason to think that learning on such a corpus will transfer to real-world texts.

As a consequence, he is interested in doing coarser formalizations. It's perfectly possible to annotate logical steps (whether as valid steps: "modus ponens", "syllogism #5", etc, or as fallacies like "affirming the antecedent", "straw man", etc.), but in practice this will need to be a bit subjective, because:
* arguments in real texts (and the sentences inside them) may be ambiguous.
* arguments in real texts almost always make use of tacit knowledge (including "common sense" knowledge).

I am uncomfortable with this subjectivity. I am more interested in normative arguments, like those found in textbooks and philosophy texts. My natural tendency is always towards fine formalizations: I want dig out the exact logical structure of the argument. (I recognize that fine formalizations are subjective too: even the proofs inside Grundlagen might potentially be interpreted in non-equivalent ways, but somehow that doesn't bother me as much. I wonder why.)

However, my advisor and I do have some intersection in interests:
* annotating argumentative/explanatory triangles (2 explicit premises, 1 conclusion) and lines (1 explicit premise, 1 hidden premise, 1 conclusion).
* annotating discourse relations ("elaboration", "explanation", "illustration", etc.)

The current plan is to annotate the blog posts that I mirrored last week (for a different purpose). I'm expecting to get very simple, disconnected lines and maybe a few triangles. I'd be (pleasantly) surprised if there are any trees deeper than that. This is not my ideal corpus, but it's a start.

My ideal corpus would be a collection of philosophical texts (although a book like Armchair Economics seems like a very rich source). Does anybody know of a source of philosophical texts in digital form?
gusl: (Default)
I've designed an XML format for the formalization of arguments. It's still very rough.

taken from Reproductive Sex as Reckless Endangerment:
Read more... )

It is an open question what set of inference tags will work best.

At first, I thought FOL rules would be enough (MP, MT, UI, etc). But even something as simple as the "Socrates is mortal" argument sits a bit awkward in that scheme: while it feels like one step to us, in FOL it's 2.

There are so many syllogistic forms, etc., which we take for granted. Sure, they could be formalized in FOL, but that's not very natural. In the case of "Socrates is mortal", the syllogism corresponds to a U.I. followed by an M.P.: but that's not how people think! The form of the syllogism precedes its formalization, so that is the right level of chunking.

The good news is that intro logic books provide tons of examples, and could serve as an initial corpus.

February 2020

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