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]