Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Templates in linguistics - Why Garbage Garbage

98 views

Published on

This is my presentation at SQUID 2014 introducing my model for language acquisition that is based mainly on templates. This started with an observation of the patterns used by my son as he was learning to speak. I included a brief survey of other areas in linguistics which also make use of templates; i.e. Information Extraction and Machine Translation.

Published in: Education
  • Be the first to comment

  • Be the first to like this

Templates in linguistics - Why Garbage Garbage

  1. 1. Templates in Linguistics: Why Garbage Garbage? Presented by: Hussein Ghaly
  2. 2. 1- Garbage Disposal Yaseen Ghaly, 3 Years Old: • Papy laih zebala zebala? (Dad, why garbage garbage?) > Why are you carrying two garbage bags? • Papy laih bang bang? (Dad, why bang bang?) > Why are you making this “bang bang/hammering” sound?
  3. 3. 2- Making a Template • Yaseen seems to be using this template: • “Papy, laih X?” (Dad, why X) • Where X can be anything: – Garbage Garbage – Bang Bang – Sleeping – … – 天空是绿色的 (foreign word/code switching)
  4. 4. 3- To build a language • How can the linguistic expression from simple sentences into language such as ours? • Answer: Recursion
  5. 5. 4- Recursively • An example of recursion found by Salma Ghaly, 6 Years old.
  6. 6. Main Claim • Language is built using simple (idiomatic) templates. The complexity comes from recursion.
  7. 7. Outline • Starting Assumptions • Learning templates (Language Acquisition) • Cross Linguistic Template Linearity • Selecting A template (Semantic-Pragmatic Prompt) • Extending A template (Template Malleability) • Applications of Templates (Information Extraction and Machine Translation)
  8. 8. Starting Assumptions - Syntax • In the syntax literature, language is a lexicon of words, and a computational system to put these words where they should form a grammatical sentence. Lexicon Computation System
  9. 9. Starting Assumptions – Templates Framework • The “lexicon”, which is stored in the memory, is extended with a list of templates, also stored in memory. • The computational system only manages what to fill the placeholders within templates. Word Lexicon Computation System Template Lexicon
  10. 10. Learning Templates • The “garbage gabage” example indicates: – A child can intuitively form a template for plurals (that is applicable in some human languages such as Bhasa Malaysia (e.g. kanak kanak=children) – A child can put anything in the placeholder X within the sentence template “Dad, Why X?” • But these hypotheses would need further evidence from First Language Acquistion
  11. 11. Template Linearity • English – I love you. – I miss you. – I need you. • French – Je t’aime. – Tu me manques. – J’ai besoin de toi. Clearly, the linear order is very different between Constructions in different languages. This should entice us to think about how these constructions are generated.
  12. 12. Semantic-Pragmatic Prompt • An area of overlap between the reason, context, and information content of some sentence. • Start with list of arguments (X1: I, X2: You) • I Want to express [+feeling] [+positive] [+distance], therefore: – in English, we invoke the template I miss X2. – In French, we invoke the template X2 me manques (with some adjustments depending on pronouns, etc) • So I can utter the sentence after filling the template: – I miss Randa. – Randa me manque.
  13. 13. Template Variability • Almost everything can be said in an alternative way: – Godzilla destroyed the City, which is unfortunate. – It is unfortunate that Godzilla destroyed the city. – The destruction of the city by Godzilla is unfortunate. • So, there are different templates to express the relation between these four entities (being unfortunate, the destruction, Godzilla, the City). This again feeds into the argument of non- linearity of templates, this time within the same language.
  14. 14. Template Malleability • Meaning how easy the template can be re- shaped. This includes the following: – Tense malleability: • John was eating fish. • John has been eating fish. – Synonym malleability: • Sarah cannot tolerate this any more. • Sarah cannot put up with this anymore. • The idea of malleability enables us to avoid accounting for hundreds of millions of combinations of basic templates.
  15. 15. Using Templates • For information Extraction (e.g. Banko and Etzioni 2008), where templates where used to extract (is-a) relationships between entities.
  16. 16. Using Templates in Machine Translation • Was first suggested by (Nagao, 1984) under the name of Example-Based Machine Translation. He also indicted this approach is relevant to Second Language Acquisition.
  17. 17. Using Templates in Machine Translation • Current state of the art Phrase-Based Statistical Machine Translation techniques uses contiguous chunks. (Koehn, 2010)
  18. 18. Using Templates in Machine Translation • But using contiguous chunks misses many phrases where there is a difference in word order between the two languages. - needs a lot of training data  • To compensate for this, a statistical reordering model is used - can make the output unintelligible 
  19. 19. Using Templates in Machine Translation Chunk: Michael assumes that he will stay in the house -> Michael geht davon aus, dass er im haus bleibt Subchunks: Michael -> Michael in the house -> im haus So by removing (stenciling) subcunks from the chunk we get a translation template X1 assumes that he will stay X2 -> X1 geht davon aus, dass er X2 bleibt - preserves word order  - can apply to many sentences not seen before  - requires less training data  - can set restrictions on the type of placeholders (X1: NP , X2: PP) 
  20. 20. •Thank X1! (X1 = You )

×