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Title: Basic Parsing with Context-Free Grammars


1
  • Basic Parsing with Context-Free Grammars

2
Analyzing Linguistic Units
  • Morphological parsing
  • analyze words into morphemes and affixes
  • rule-based, FSAs, FSTs
  • Ngrams for Language Modeling
  • POS Tagging
  • Syntactic parsing
  • identify constituents and their relationships
  • to see if a sentence is grammatical
  • to assign an abstract representation of meaning

3
Syntactic Parsing
  • Declarative formalisms like CFGs define the legal
    strings of a language -- but dont specify how to
    recognize or assign structure to them
  • Parsing algorithms specify how to recognize the
    strings of a language and assign each string one
    (or more) syntactic analyses
  • Parsing useful for grammar checking, semantic
    analysis, MT, QA, information extraction, speech
    recognitionand almost every task in NLP

4
Parsing as a Form of Search
  • Searching FSAs
  • Finding the right path through the automaton
  • Search space defined by structure of FSA
  • Searching CFGs
  • Finding the right parse tree among all possible
    parse trees
  • Search space defined by the grammar
  • Constraints provided by the input sentence and
    the automaton or grammar

5
CFG for Fragment of English
S ? NP VP VP ? V
S ? Aux NP VP PP -gt Prep NP
S ? VP N ? book flight meal money
NP ? Det Nom V ? book include prefer
NP ?PropN Aux ? does
Nom ? N Nom Prep ?from to on
Nom ? N PropN ? Houston TWA
Nom ? Nom PP Det ? that this a
VP ? V NP
LCs
TopD BotUp
E.g.
6
S VP NP Nom V Det
N Book that flight
Parse Tree for Book that flight for Prior CFG
7
Rule Expansion
Det ? that this a
LCs
TopD BotUp
E.g.
8
Top-Down Parser
  • Builds from the root S node to the leaves
  • Assuming we build all trees in parallel
  • Find all trees with root S (or all rules w/lhs S)
  • Next expand all constituents in these trees/rules
  • Continue until leaves are pos
  • Candidate trees failing to match pos of input
    string are rejected (e.g. Book that flight
    matches only one subtree)

9
Top-Down Search Space for CFG (expanding only
leftmost leaves)
S S S NP VP Aux NP VP VP S
S S S S S NP VP NP VP Aux NP
VP Aux NP VP VP VP Det Nom PropN Det
Nom PropN V NP V Det
Nom N
10
Bottom-Up Parsing
  • Parser begins with words of input and builds up
    trees, applying grammar rules whose rhs match
  • Book that flight
  • N Det N V Det N
  • Book that flight Book that flight
  • Book ambiguous (2 pos appear in grammar)
  • Parse continues until an S root node reached or
    no further node expansion possible

11
Two Candidates One Successful Parse
  • S
  • VP
  • VP NP NP
  • Nom Nom
  • V Det N V Det N
  • Book that flight Book that flight

S ? VP NP
12
Whats right/wrong with.
  • Top-Down parsers they never explore illegal
    parses (e.g. which cant form an S) -- but waste
    time on trees that can never match the input
  • Bottom-Up parsers they never explore trees
    inconsistent with input -- but waste time
    exploring illegal parses (with no S root)
  • For both find a control strategy -- how explore
    search space efficiently?
  • Pursuing all parses in parallel or backtrack or
    ?
  • Which rule to apply next?
  • Which node to expand next?

13
A Possible Top-Down Parsing Strategy
  • Depth-first search
  • Agenda of search states expand search space
    incrementally, exploring most recently generated
    state (tree) each time
  • When you reach a state (tree) inconsistent with
    input, backtrack to most recent unexplored state
    (tree)
  • Which node to expand?
  • Leftmost or rightmost
  • Which grammar rule to use?
  • Order in the grammar? How?

14
Top-Down, Depth-First, Left-Right Strategy
  • Initialize agenda with S tree and ptr to first
    word and make this current search state (cur)
  • Loop until successful parse or empty agenda
  • Apply all applicable grammar rules to leftmost
    unexpanded node of cur
  • If this node is a POS category and matches that
    of the current input, push this onto agenda
  • O.w. push new trees onto agenda
  • Pop new cur from agenda
  • Does this flight include a meal?

15
Fig 10.7
CFG
16
Left Corners Top-Down Parsing with Bottom-Up
Filtering
  • We saw Top-Down, depth-first, L2R parsing
  • Expands non-terminals along the trees left edge
    down to leftmost leaf of tree
  • Moves on to expand down to next leftmost leaf
  • Note In successful parse, current input word
    will be first word in derivation of node the
    parser currently processing
  • So.look ahead to left-corner of the tree
  • B is a left-corner of A if A gt B
  • Build table with left-corners of all
    non-terminals in grammar and consult before
    applying rule

17
Left Corners
18
Left-Corner Table for CFG
19
Left Recursion vs. Right Recursion
  • Depth-first search will never terminate if
    grammar is left recursive (e.g. NP --gt NP PP)

20
  • Solutions
  • Rewrite the grammar (automatically?) to a weakly
    equivalent one which is not left-recursive
  • e.g. The man on the hill with the telescope
  • NP ? NP PP (wanted Nom plus a sequence of PPs)
  • NP ? Nom PP
  • NP ? Nom
  • Nom ? Det N
  • becomes
  • NP ? Nom NP
  • Nom ? Det N
  • NP ? PP NP (wanted a sequence of PPs)
  • NP ? e
  • Not so obvious what these rules mean

21
  • Harder to detect and eliminate non-immediate left
    recursion
  • NP --gt Nom PP
  • Nom --gt NP
  • Fix depth of search explicitly
  • Rule ordering non-recursive rules first
  • NP --gt Det Nom
  • NP --gt NP PP

22
The city hall parking lot in town
  • NP? NP NP PP
  • NP ? Det Nom
  • NP ? Adj Nom
  • NP ? Nom Nom
  • Nom ? NP Nom
  • Nom ? N
  • PP ? Prep NP
  • N ? city hall lot town
  • Adj ? parking
  • Prep ? to for in

23
Structural ambiguity
  • Multiple legal structures
  • Attachment (e.g. I saw a man on a hill with a
    telescope)
  • Coordination (e.g. younger cats and dogs)
  • NP bracketing (e.g. Spanish language teachers)

24
NP vs. VP Attachment
25
  • Solution?
  • Return all possible parses and disambiguate using
    other methods

26
Summing Up
  • Parsing is a search problem which may be
    implemented with many control strategies
  • Top-Down or Bottom-Up approaches each have
    problems
  • Combining the two solves some but not all issues
  • Left recursion
  • Syntactic ambiguity
  • Next time Making use of statistical information
    about syntactic constituents
  • Read Ch 11
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