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Interpreting Dictionary Definitions

Interpreting Dictionary Definitions. Dan Tecuci May 2002. Problem Description. Interpretation = translating into one's own language Given : Dictionary definitions of actions KB = set of primives/components Argument structure Text generation Axioms Pre/post/during conditions

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Interpreting Dictionary Definitions

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  1. Interpreting Dictionary Definitions Dan Tecuci May 2002

  2. Problem Description • Interpretation = translating into one's own language • Given: • Dictionary definitions of actions • KB = set of primives/components • Argument structure • Text generation • Axioms • Pre/post/during conditions • User input • Produce • Representations of actions

  3. Example • Dictionary: carry = to move while supporting • Challenges: • Identify what primitive components are referred • Move, Support • Deal with missing arguments • An agent moves an object while supporting it • Resolve references between them • Agent1 moves object2 while Agent1 supports object2 • Identify deep semantic relations among them • There are two subevents of Carry, one in which Agent1 moves object2 and one in which Agent1 supports object2 so that object2 cannot fall, and they happen in parallel

  4. What Is the Goal? • Acquire different kinds of knowledge: • Taxonomic • Semantics of actions • Argument structure • In order to: • Accelerate knowledge acquisition • Execute actions • Talk about them • Understand when someone talks about them

  5. Knowledge of Argument Structure • What arguments does the verb have and where they surface (position) • Multiple ways in which an argument can surface. – • E.G. • V+o[+a] -> carry something [somewhere]. • The reverse of text-gen

  6. Motivation • Why this task • Fast, automatic knowledge acquisition • Language understanding and generation • Available source of knowledge • Why dictionaries • Structured source of knowledge • Taxonomic • Argument structure • Could be extended to full natural language • Has been done before (manually)

  7. Related Work - R. Amsler • "The structure of MW dictionary" 80 • Analyses definitions based on “kernels” (superclasses) • Main goal - build a taxonomy of motion verbs • Other • Procedure to analyse the argument structure of motion verbs (look at usage in other definitions and use componential analysis) • Manual WSD, manual kernel identification, automatic taxonomy building

  8. Related Work - C. Barrière • “From a children dictionary to a LKB” • Automatic translation of dictionary definitions into a knowledge representation formalism • Specifics • Uses an intermediary representation • Only 1 sense of a word is analysed • Children dictionary has usage examples

  9. Related Work - C. Hastings • Tries to acquire word (mainly verb) meaning from context (sentence) • Uses LINK parser, semantic knowledge, terrorism domain • KB has detailed info, fine-grained constraints • Uses rules based on sentence structure to detect case-role assignment • Syntactic/semantic knowledge is expressed in the same formalism (LINK) • Algorithm: • Identify slot fillers • Based on this, identify matching components

  10. Related Work - FrameNet • Mainly the same goal, but bottom-up • Not based on composing a set of primitives • Manually annotate sentences, automatically capture the organization of the annotation results • Frame – • frame elements • How FEs are realized in language • Executable?

  11. Dictionary Definitions • Advantages • Good source of taxonomic knowledge • Follow a “genus-differentia” pattern • Some dictionaries tend to define everything in terms of a basic vocabulary • Disadvantages • Definitions are elliptical • Incomplete sentences (not easier to parse then NL) • Leave blank argument positions that are nearly always filled in usage • One definition does not provide enough info

  12. What We Need • What kind of knowledge do we need for such a task? • Knowledge about primitive components • Semantic - meaning • Syntactic - argument structure • How to determine when a concept is referenced? • Knowledge about how to compose them and how this is reflected in language

  13. Complex Actions • What are complex actions? • How to discover them? • Dictionaries

  14. Example - Steps • Carry = to move while supporting • Steps: • Identify referenced concepts/components • Identify their arguments • How are the components assembled • Resolve references • Get knowledge about argument structure

  15. Identifying components Example: move #1, support#4 Move, Support

  16. Identifying the arguments • Arguments of Move, Support? • From • definition • Problem: definitions omit args that are usu. present • KB • Minimal number of required args • Arguments of Carry • Suggested by: • syntax • dictionary: transitive/intransitive • definitional patterns - Carry ISA Move • How are they related ?

  17. Assembling the components • Meaning of the whole = function of parts and the way they are composed • Discover deep semantic relations among components referenced • Prepositions – clues • Example: • “while” – co-temporality or detraction • “by”- by-means-of, agent, time, location… • Rules based on features of components • How to test if a component is correct/coherent? (test-cases?)

  18. Resolving co-references • What object are co-referential? the agent of Move = the agent of Support the object of Move = the agent of Support • How to do it? • Heuristic – assume everything maps unchanged unless there is reason to believe otherwise • Matching • Machine learning

  19. KB • Move • 16 senses in WN 1.6 • 8 represented in CompLib – tr. & intr. • What about argument structure? • Multiple argument structure can correspond to a sense • Argument structures • Subj + Move => agent ~ Subj • Subj + Move + DObj => agent ~ Subj, object ~ object • …

  20. KB (cont.) – Arg Struct for Move • Full arg structure for Move “agent moves object over distance using instrument along path from source to destination” • How to • Acquire such knowledge? • Express it? • All possible trees • Constraints (Subj always before Pred.)

  21. Observations • Verb definitions differ in level of generality • More general - elliptical definitions • “Carry = move while supporting” • Inherit more from primitive components • More specific - more complete definitions • “Bioremediation = treating waste or pollutants by the use of microorganisms (as bacteria) that can break down the undesirable substances” • Highly specialized versions of supers

  22. What's next • Focus on a subproblem (e.g. WSD) • Get data (FrameNet?) • Design an experiment • Compare to existing methods

  23. Research questions • What dictionary to use? (WN?) • How to represent arg struct knowledge? • How would the special nature of the knowledge we have might help in this task? • actions can be executed • their results can be tested • Does compositionality help?

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