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NLP > Constituency Grammars > Flashcards

Constituency Grammars Flashcards

1
Q

What does syntax mean?

A

It is the way words are arranged together

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2
Q

What does syntactic consistency mean?

A

It is the idea that words can be grouped into single units (e.g. Noun Phrase)

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3
Q

How do we form constituents?

A

We use evidence from the context of the sentence to group words to form them

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4
Q

What is a constituent?

A

It is a word or group of words that function as a single unit

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5
Q

How can evidence be encoded?

A

In rules or grammars

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6
Q

What are some different Grammar types?

A

Context Free Grammar (CFG)

Dependency Structure Grammar

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7
Q

What are some features of a CFG?

A

Rules are based on phrasal constituents + phase-structure

Word order is very important

Head terms are embedded into trees making it harder to find

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8
Q

What are some features of a Dependency Structure Grammar?

A

Rules are based on grammatical dependencies between words

Word order is flexible

(Head → Dependent) approximates the semantic relationship between predicates and arguments

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9
Q

State which of the graphs show a CFG and a Dependency Grammar.

A

The left is a Dependency Grammar

The right is a CFG

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10
Q

Explain what the graph generated using CFG shows.

A

The root node, S, is saying we have a sentence, and for this parse tree the sentence will have a noun phrase followed by a verb phrase. We can see that the noun phrase consists of a pronoun, which we can see is ‘I’. We can see that the verb phrase consists of a verb and noun phrase. This continues until we reach all the leaf nodes.

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11
Q

What are the leaf nodes typically in a CFG graph?

A

They are typically lexical terms (words)

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12
Q

What are dependency grammars based on?

A

They are based on the subject-object relationship.

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13
Q

What does a context free grammar model?

A

It models constituent structure

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14
Q

What two things does a CFG have?

A

A lexicon (of words and symbols)

A set of rules (or productions)

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15
Q

What form are CFG rules equivalent to?

A

Backus-Naur Form (BNF)

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16
Q

How are CFG rules embedded, and what does it allow them to do?

A

They are hierarchically embedded, meaning that they can trigger other rules

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17
Q

Explain how the productions work in the image.

A

Given a left symbol, generate a right set of symbols.

One derivation is where you follow the productions all the way through

The productions can actually be recursive

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18
Q

What are some typical CFG production rules?

A

Leaf nodes are terminal nodes

Non-terminal nodes define lexical categories (POS)

A node is said to dominate its child nodes

The root node is the start symbol (usually ‘S’)

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19
Q

What do we call sentences that can and cannot be derived from a CFG?

A

Can be derived are called grammatical, cannot be derived are called ungrammatical

20
Q

Why is a CFG a generative grammar?

A

The language is defined by the possible sentences it can generate

21
Q

What is the problem of mapping sentences to parse trees called?

A

Syntactic parsing

22
Q

What does a declarative sentence mean?

A

We have a subject NP followed by an VP

S → NP VP

23
Q

What does an imperative level sentence mean?

A

There is a VP with no subject

S → VP

24
Q

What does a yes-no question form mean?

A

There is an auxiliary verb followed by a subject NP and a VP

S → Aux NP VP

25
Q

What does a wh-subject-question mean?

A

There is a wh-word followed by a subject NP and a VP

S → Wh-NP VP

26
Q

What does a wh-non-subject-question mean?

A

It is where the wh-phrase is not the subject

S → Wh-NP Aux NP VP

27
Q

What is a wh-non-subject-question an example of?

A

A long distance dependency - the Wh-NP is far away from the semantically relevant main VP

28
Q

What can sentences consist of?

A

One or more clauses

29
Q

What is a clause?

A

It is a ‘complete thought’

30
Q

What is a clause made up of?

A

Two or more of:

  • Subject
  • Verb
  • Object
  • (Subject|Object) Complement
  • Adverbial
31
Q

What are clauses critical for?

A

Applications such as relation extraction

32
Q

What do noun phrases consist of?

A

A head noun and various modifiers

33
Q

What can determiners be?

A

Simple lexical terms like a, the, this.

Or they can be more complex with possessive markers (‘s)

34
Q

What is a nominal?

A

It is typically a head noun and optional noun modifiers which can occur before or after the head noun

Nominal → Noun | NUM Nominal | Nominal PP | (who|what) VP

35
Q

What is verb phrase typically?

A

A VP plus a number of other constituents

VP → VP | Verb NP PP | Verb NP | Verb PP

36
Q

What are sequential compliments?

A

These are VP followed by an embedded sentence

VP → Verb S

37
Q

What do traditional grammars do with verbs?

A

Subcategorise the verbs into a few categories

38
Q

What are some verb categories?

A

Transitive Verbs - object

Intransitive Verbs - no object

Ditransitive Verbs - direct and indirect object

Linking Verbs - links clause subject with complement

39
Q

What is different about what modern grammars do with verbs?

A

They can have up to 100 subcategories of verbs. Sets of complements are called the subcategorisation frame

40
Q

What are coordinations?

A

These are conjunctions such as and, or, but

VP → NP and NP

Nominal → Nominal and Nominal

S → S and S

VP → VP and VP

41
Q

What is a treebank?

A

A treebank is a syntactically annotated corpus. They have tagsets based on linguistic annotation choices from the authoring project

42
Q

How are long distance dependencies (syntactic movement) encoded in tagsets?

A

They are encoded using -NONE- markers

43
Q

How many rules types and words does Treebank 3 have?

A

17,500 rule types and a million words

44
Q

What is a lexical head?

A

A lexical head is the word in a phrase which is grammatically the most important - they can be tricky to define as they are context dependent. In practice, handwritten rules are used guided by statistical analysis

45
Q

What grammar emphasises lexical features over phrase-structure?

A

Combinatory Categorical Grammar (CCG) - defines categories and has mappings between lexicon words to categories, can go forward and backwards. Is very powerful

NLP (20 decks)

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