Systematic Mismatches Across Annotations

1
Systematic Mismatches Across Annotations

• Alan Lee and Aravind Joshi
• Institute for Research in Cognitive Science
  Department of Computer and Information Science,
  University of Pennsylvania
• ULA Workshop,
• U of Colorado, Boulder
• March 2008

2
Preliminaries

• We observe that certain annotated features of the
  Penn Discourse Treebank 2.0 (PDTB) do not match
  up neatly with annotations at the syntactic
  level.
• What do certain mismatches suggest for linguistic
  theory? How do we get from syntax to discourse?
• How does this affect NLP applications?

3
Outline

• Attribution spans
• Parallel Connectives
• AltLex
• Polarity and Determinacy

4
Outline

• Attribution spans
• Parallel Connectives
• AltLex
• Polarity and Determinacy

5
Attribution Spans

• Relation between agents and abstract objects
  (discourse relations or their arguments)
• Annotation Text Spans and Four features
  (source, type,
• polarity, determinacy). More on the features
  later.

6

• There have been no orders for the Cray-3 so far,
  though the company says it is talking with
  several prospects.
• Discourse semantics contrary-to-expectation
  relation between there being no orders for the
  Cray-3 and there being a possibility of some
  prospects.
• Sentence semantics contrary-to-expectation
  relation between there being no orders for the
  Cray-3 and the company saying something.

7

• Although takeover experts said they doubted Mr.
  Steinberg will make a bid by himself, the
  application by his Reliance Group Holdings Inc.
  could signal his interest in helping revive a
  failed labor-management bid.
• Discourse semantics contrary-to-expectation
  relation between Mr. Steinberg not making a bid
  by himself and the RGH application signaling
  his bidding interest.
• Sentence semantics contrary-to-expectation
  relation between experts saying something and
  the RGH application signaling Mr. Steinbergs
  bidding interest.

8

• Mismatches occur with other relations as well,
  such as causal relations
• Investors are nervous about the issue because
  they say the company's ability to meet debt
  payments is dependent on too many variables,
  including the sale of assets and the need to
  mortgage property to retire some existing debt.
• Discourse semantics causal relation between
  investors being nervous and problems with the
  companys ability to meet debt payments
• Sentence semantics causal relation between
  investors being nervous and investors saying
  something!

9
How to address mismatch?

• One possibility - treat attribution as a
  different layer of structure in discourse. (and
  also in syntax?)
• This has the effect of reducing the complexity of
  the discourse structure.

10
Discourse Graphbank (Wolf Gibson 2005)

• Farm prices in October edged up 0.7 from
  September
• as raw milk prices continued their rise,
• the Agriculture Department said.
• Milk sold to the nation's dairy plants and
  dealers averaged 14.50 for each hundred pounds,
• up 50 cents from September and up 1.50 from
  October 1988,
• the department said.

11
sim
elab
attr
attr
1-2
4-5
1
2
3
4
5
6
ce
elab
ce - cause/effect elab - elaboration sim -
similiarity attr - atribution
12
elab
1-2
4-5
1
2
3,attr
4
5
6,attr
ce
elab
ce - cause/effect elab - elaboration sim
- similiarity attr - atribution
13
Residual issues
Does attribution scope over the entire relation,
or just Arg1?
Even if B.A.T receives approval for the
restructuring, the company will remain in play,
say shareholders and analysts, though the
situation may unfold over the next 12 months,
rather than six.
Arg1 attributed to shareholders and
analysts Rel and Arg2 attributed to Writer
Guideline in case of doubt, attribute to the
Writer
14
Residual issues

• Attribution cannot always be excluded by default
• Advocates said the 90-cent-an-hour rise, to 4.25
  an hour by April 1991, is too small for the
  working poor, while opponents argued that the
  increase will still hurt small business and cost
  many thousands of jobs.

What implications does this have for the approach
of treating attribution as an independent layer
of discourse?
15
Outline

• Attribution spans
• Parallel Connectives
• AltLex
• Polarity and Determinacy

16
Parallel Connectives

• Either he wasnt being real in the past or he
  isnt being real right now. (1549)
• Youve either got a chair or you dont. (2428)
• If the answers to these questions are
  affirmative, then these institutional investors
  are
• likely to be favorably disposed toward a specific
  poison pill. (0275)
• Parallel connectives are annotated
  discontinuously
• In the PDTB, both parts of a parallel connective
  are treated as equally prominent (no hierarchical
  relationship)

17
In Penn Treebank, the treatment of a parallel
connective depends on its position within
sentence. When Either is sentence-initial,
both either and or are annotated as CC.

• Either he wasnt being real in the past or he
  isnt being real right now. (wsj_1549)

S
S
S
CC
CC
Either
he wasnt being real in the past
or
he isnt being real right now
18
This is not possible when either is
sentence-medial. Here, either is treated as an
RB and or is as a CC.

• Youve either got a chair or you dont.
  (wsj_2428)

S
S
S
CC
or
NP-SBJ
VP
ADVP
VP
you dont
RB
You
ve
got a chair
either
19

• How to represent parallel connective?
• DL-TAG approach elementary discourse tree with
• two lexical anchors (DC discourse clause)

DC
DC
Either
DC?
or
DC?
because
DC?
DC?
But question remains how to transition from
syntactic structure to discourse structure?
20
Outline

• Attribution spans
• Parallel Connectives
• AltLex
• Polarity and Determinacy

21
Alternative Lexicalization(AltLex)

• A discourse relation is inferred between two
  sentences which do not contain an Explicit
  connective, but insertion of an Implicit
  connective leads to redundancy. This is because
  the relation is alternatively lexicalized by some
  non-connective expression
• Under a post-1987 crash reform, the Chicago
  Mercantile Exchange wouldnt permit the December
  SP futures to fall further than 12 points for a
  half hour. AltLex (consequence) That caused a
  brief period of panic seeling of stocks on the
  Big Board.

22
Discourse Connectives and Syntactic Constituency

• Most explicit connectives correspond to syntactic
  constituencies. E.g. (because IN, but CC,
  as a result PP, etc.)
• Some small exceptions with parallel connectives,
  as we have seen.

23

• AltLex expressions often do not correspond to
  syntactic constituencies.
• Under a post-1987 crash reform, the Chicago
  Mercantile Exchange wouldnt permit the December
  SP futures to fall further than 12 points for a
  half hour. AltLex (consequence) That caused a
  brief period of panic selling of stocks on the
  Big Board.

S
NP-SBJ
VP
VBD
DT
DT
PP-LOC
That
caused
a brief period
of panic selling..
24

• For a list of AltLex expressions annotated in
• the PDTB
• http//www.seas.upenn.edu/pdtb/altlex-strings.txt
  
• Or search using PDTB Browser (shameless
• plug)
• http//www.seas.upenn.edu/pdtb/PDTBAPI/pdtbbrowse
  r.jnlp

25
Outline

• Attribution spans
• Parallel Connectives
• AltLex
• Polarity and Determinacy

26
Attribution Features

• Attribution is annotated on relations and
  arguments, with FOUR
• Features.
• Source encodes the different agents to whom
  proposition is attributed
• Wr Writer agent
• Ot Other non-writer agent
• Arb Generic/Atbitrary non-writer agent
• Inh Used only for arguments attribution
  inherited from relation
• Type encodes different types of Abstract Objects
• Comm Verbs of communication
• PAtt Verbs of propositional attitude
• Ftv Factive verbs
• Ctrl Control verbs
• Null Used only for arguments with no explicit
  attribution

27
Polarity vs Determinacy

• Polarity Indicates narrow scope of surface
  negated attributions.
• (Neg-raising, Klima 1964). Marked as Neg when
  neg-raising
• occurs. Null otherwise.
• John doesnt think the book fell ( John thinks
  the
• book didnt fall)
• Determinacy Attributions rendered indeterminate
  in certain
• contexts. Marked as Indet, or Null otherwise.
• John didnt say the book fell ( no lowering of
  negation)
• Only a certain class of verbs can have negative
  polarity,
• i.e. induce neg-raising. Verbs of Propositional
  Attitude (PAtt)
• have this behavior, but not others.

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Polarity vs Determinacy

• I dont believe they have the culture to
  adequately service high-net-worth individuals.
  (0927)
• Discourse semantics
• I believe they DO NOT have the culture to
  adequately service high-net-worth individuals.
  (0927)
• Negation of expect is lowered onto the
  argument. The attribution is marked as negative
  polarity.
• Note that the attribution event of expecting
  did occur (is determinate).

29
Polarity vs Determinacy

• It didnt say if its earlier results were
  influenced significantly by nonrecurring
  elements. (1711)
• Negation of say is NOT lowered onto the
  argument. The attribution is marked as
  indeterminate.
• The attribution event (of saying) did not
  actually occur.

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At Syntactic Level

• At which level should discrepancy in the
  polarity vs determinacy type of
• negation be captured?
• - In PropBank, negations of attribution verbs are
  uniformly marked as a
• negative feature for the adjunct feature ARGM.
  
• - In TimeML, they contain a polarity feature of
  Neg.
• I dont BELIEVE they have the culture to
  adequately service high-net-worth individuals.
• ARG1 I
• ARG2 they have the culture
• ARGM Neg (PropBank) No Neg for lower predicate
  have
• POLARITY Neg (TimeML)
• Should the negation be marked as ARGM for the
  lower predicate
• (have) instead?

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At Syntactic Level

• It didnt SAY if its earlier results were
  influenced significantly
• by nonrecurring elements.
• ARG1 It
• ARG2 if its earlier results were influenced
  significantly
• by nonrecurring elements
• ARGM Neg (PropBank)
• POLARITY Neg (TimeML)
• Saying event is indeterminate. Does this still
  count as an event?
• How to order this temporally?

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Some questions

• How much of discourse is projected from syntax?
• Is there a need for a different architecture,
  different building blocks?
• How are these issues manifested
  cross-linguistically? Currently, discourse
  annotation work being done for Hindi, Turkish,
  Czech and Finnish (possibly).