Teaching old-school semantics to new people who are trying to reinvent semantics

Alexander and Dan’s notes from Oslo:

places where the simple syn-sem homomorphism breaks down
types are needed to ensure that the output representation is interpretable (even when there are diff semantic formalisms)
existing mechanisms for dealing with scope (as one example of non-homomorphism)
semantic ambiguities and how to deal with them
semcon methods for different syntax formalisms
compositionality and its limits
ugly corner cases: comparatives; plural/distributivity
continuum from syntax to semantics; injecting mild bits of semantics into syntactic representations (e.g. enhanced UD); where do you draw the line?
need to normalize meaning representations to use them for inference; either in grammar or in KB. Advantages? Problem also arises in cross-lingual information extraction. Can you believe in an interlingua, and if not, what do you do instead, pragmatically?
Certain things are simple and solved and don’t need to be reinvented.
Control != anaphora.
lexicon-grammar tradeoff
how do you test a theory with problematic examples

Points in discussion:

Tests for semantic contrasts: downward vs. upward monotonic quantifiers. Donkey sentences -> how do indefinites work. Established example sentences for identifying quicksand.
Negation and modals in English (“John can’t leave” vs “John mustn’t leave” - not(can), must(not)).
Collect repository of hard sentences/minimal pairs that illustrate important semantic pitfalls.
“Fixing semantics” post-hoc may be easier if the syntax is already designed correctly.
Thematic roles and word senses: before you figure them out, you can’t do inference.
Picture-based corpora only show you things that exist in the real world; no quantifiers or weird negations needed. No intensionality needed. A veridical

universe.

e.g. “regret” vs “wonder” (whether the embedded clause refers to an existing situation)
One way of organizing material top-down: go by task? E.g. if you want to do QA, here are some problems you will run into. What kind of monsters are particularly scary for which quests?
Cross-linguistic issues? Swimming across lake vs. crossing lake by swimming; POS mismatches; different idioms.
How much paraphrasing should sem rep normalize? AMR vs. MRS.
Even “and” and “not” in English don’t usually translate directly to logical operators.
Push some problems down to pragmatics. Where do you draw the line?
Semantics has a lot of layers; Emily’s distinction between “sentence meaning” and “speaker meaning” in context; Alex L’s distinction between public commitments and what can be inferred about what the speaker things but they aren’t publicly committed to
Solved problems vs. well-studied but unsolved problems
Even adjuncts vs. arguments is a thing that computer scientists may not know about, but should.
Focus on practical approaches/solutions/challenges. Sidesteps both CS criticism that linguistics gets bogged down in pointless debates, and linguist criticism that we are not doing the phenomena full justice. We are grammar _engineers_, not just pure linguists.

“Linguistic beasts and how to tame them”

Video lectures could be useful resource. Be sure to break them up into short segments (7 min) so people can navigate.
Volunteers for providing content: Emily; Francis; Francis’s minions; Antske
Other people who might provide something: Johan; Cleo
Aim at 20 articles before next DELPH-IN meeting

What to do about this

Emily’s “100 things” book(s)
Find a way to make contents of the book turn up in Google searches
Crowdsourced collection of annotated examples?
For syntax, there is http://test.terraling.com/groups/7; do similar resources for semantics exist? Task-based?
Use ERG-based parser as a frontend that points out interesting constructions in your sentence and links to pertinent pages?
High-level short list of problems (at syntax-semantics interface)
ACL tutorial, with video lecture?
Series of short videos (~7mins)?
WikiBook

Last update: 2018-06-21 by AlexanderKoller [edit]