Feature Structures and Unification in Linguistic Theory: A Study of Pizza and Grammar, Study notes of Linguistics

The use of feature structures and unification in linguistic theory through the example of pizza. It covers the earley parser, problems with context-free grammars (cfg), and the solution of replacing atomic node labels with feature structures. The document also introduces some grammatical theories that use feature structures and unification, such as gpsg, hpsg, lfg, and construction grammar. It provides a pizza type hierarchy and explains how to represent pizza descriptions and models using unification.

Typology: Study notes

Pre 2010

Uploaded on 03/18/2009

koofers-user-354
koofers-user-354 🇺🇸

4

(1)

10 documents

1 / 56

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
May 12, 2008
Chapter 11
Feature structures, Unification
1
pf3
pf4
pf5
pf8
pf9
pfa
pfd
pfe
pff
pf12
pf13
pf14
pf15
pf16
pf17
pf18
pf19
pf1a
pf1b
pf1c
pf1d
pf1e
pf1f
pf20
pf21
pf22
pf23
pf24
pf25
pf26
pf27
pf28
pf29
pf2a
pf2b
pf2c
pf2d
pf2e
pf2f
pf30
pf31
pf32
pf33
pf34
pf35
pf36
pf37
pf38

Partial preview of the text

Download Feature Structures and Unification in Linguistic Theory: A Study of Pizza and Grammar and more Study notes Linguistics in PDF only on Docsity!

May 12, 2008

Chapter 11

Feature structures, Unification

1

Overview

Leftovers: Earley parser

Problems with CFG

One solution: feature structure and unification

An aside on modeling language

Practice with unification (pizza)

Concepts relating to feature structures

Feature structures in the grammar

Using types to capture linguistic generalizations

2

The Earley Chart Parser, Features

One pass through the chart/sentence

Recognizer, which can be modified into a parser

Top-down, uni-directional, exhaustive (as parser)

4

Discussion: How does the Earley algorithm solve

these problems?

Ambiguity

Inefficient reparsing of subtrees

Infinite loops with left-recursive grammars

NP

NP PP

The cat on the mat by the door slept

5

Problems with CFG

Potentially arbitrary rules: D

S VP

return to this)Gets clunky quickly with cross-cutting properties (we’ll

(Not quite powerful enough for natural languages)

Solution: Replace atomic node labels with feature structures.

7

Some grammatical theories which explicitly use

feature structures and unification

GPSG: Generalized Phrase Structure Grammar

http://hpsg.stanford.edu/HPSG: Head-driven Phrase Structure Grammar

http://www-lfg.stanford.edu/lfg/LFG: Lexical Functional Grammar

http://www.constructiongrammar.org/Construction Grammar

Combinatory Categorial Grammar

8

Modeling language (HPSG)

Three things involved in modeling:

Real-world entities

Models

Descriptions of models

10

Feature Structure Descriptions

FEATURE

1

VALUE

1

FEATURE

2

VALUE

2

FEATURE

n

VALUE

n  

11

TYPE

FEATURES/VALUES

IST

pizza pizza-thing

CRUST

thick, thin, stuffed

TOPPINGS

topping-set

pizza-thing

topping-set

OLIVES

ONIONS

MUSHROOMS

pizza-thing

vegetarian

topping-set

non-vegetarian

SAUSAGE

PEPPERONI

HAM

topping-set

13

Type Hierarchies

A type hierarchy...

types).... states what kinds of objects we claim exist (the

shared properties (the IST relations).... organizes the objects hierarchically into classes with

(the feature and feature value declarations).... states what general properties each kind of object has

14

Pizza Descriptions and Pizza Models

CRUST pizza

thick

TOPPINGS

OLIVES vegetarian

ONIONS

CRUST , thick

TOPPINGS ,

OLIVES ,

ONIONS ,

MUSHROOMS ,

CRUST , thick

TOPPINGS ,

OLIVES ,

ONIONS ,

MUSHROOMS ,

16

Pizza Descriptions and Pizza Models

CRUST pizza

thick

TOPPINGS

OLIVES vegetarian

ONIONS

‘type’/‘token’ distinction – applies to sentences as wellcorrespond to? How many pizzas-in-the-world do the pizza models

17

Unification

CRUST^ pizza

thick

TOPPINGS

OLIVES

ONIONS

HAM

19

Unification

CRUST pizza

thick

TOPPINGS

OLIVES

HAM

CRUST^ pizza

thin

TOPPINGS

OLIVES

ONIONS

20