micro-propositions as a basis for deep text understanding...propositions can be decomposed...

Micro-propositions as a basis for deep textunderstanding

Chantal van Son, Lora Aroyo, Roser Morante, Piek Vossen

VU Amsterdam

December 15, 2017

Second International Symposium on Cross-disciplinary Research in the Health Humanities and Beyond:

Perspectives and Knowledge Landscapes in the Digital Health Society

van Son et al. (VU Amsterdam) Micro-propositions for text understanding December 15, 2017 1 / 25

Outline

Outline I

1 Introduction

2 Texts as collections of propositions

3 Perspectives: attribution & factuality

4 Micro-propositionsWhat are micro-propositions?Why do we need micro-propositions?

5 Future directions


Introduction

Outline

1 Introduction




5 Future directions


Introduction

Introduction

Much medical and health-related information is found online in the formof text (unstructured data)

Large variety of sources with different backgrounds and motivations

Result: complex debate about what is true and what is not

Direct: explicit (dis)agreement with previously made statementsIndirect: distributing contradictory or affirmative statements

Difficult for citizens, researchers and medical professionals to obtain areasonable overview of existing beliefs

Today: examples from the vaccination debate


Introduction

Fast-forward: the goal

GOAL: Automatically extracting and comparing beliefs/statements fromtexts using Natural Language Processing

Mike Adams(NaturalNews)

VACCINES ARE INEFFECTIVE

VACCINES ARE TOXIC

VACCINES CAUSE DEATH

VACCINES ARE UNNECESSARY

ADVERSE REACTIONS ARE FREQUENT

VACCINES CAUSE AUTISM

VACCINES CAUSE OUTBREAKS

Centers for Disease Controland Prevention

VACCINES ARE EFFECTIVE

VACCINES ARE SAFE

VACCINES SAVE LIVES

VACCINES ARE NECESSARY

ADVERSE REACTIONS ARE RARE

VACCINES PREVENT ILLNESSES

LOW VACCINATION RATES CAUSE OUTBREAKS

+ attitude of source towards statement

+ relations between statements (and indirectly: between sources)


Introduction

Rewind: the reality

Mike Adams (NaturalNews)

While the media continues to spew emotionally charged tirades about how theanti-vaccination “movement” allegedly triggered the recent measles outbreak thathealth authorities believe started at Disneyland, actual science suggests that themost likely cause of this insanely overblown outbreak was a person who was recentlyvaccinated. Numerous published studies reveal how live-virus vaccines like MMR(measles, mumps and rubella) actually shed these diseases for many weeks or evenmonths following vaccination, potentially infecting others, both vaccinated andunvaccinated. This means that any child who was recently given an MMR vaccineis a walking disease-spreader, a truth that the media is refusing to report as evenjust a possibility in this case.


Introduction

Rewind: the reality

Centers for Disease Control and Prevention

High population immunity secondary to high measles vaccination coverage hasmaintained measles elimination in the United States since declaration of eliminationin 2000 (5). Worldwide, however, approximately 20 million measles cases occurannually, and importations to the U.S. will continue to place unvaccinatedpopulations at risk for measles. Measles transmission in pockets of unvaccinatedpersons increases the risk for transmission to vulnerable groups, such as those whocannot be vaccinated because of underlying medical conditions, or infants tooyoung to be vaccinated.

Both texts are talking about the cause of measles outbreaks(vaccines/unvaccinated)

So how do we get from these complex and unstructured texts to conciseand understandable statements that we can reason over and compare?


Texts as collections of propositions

Outline

1 Introduction




5 Future directions



Propositions

Texts are collections of propositions having reference to events, entitiesand properties in the (real or assumed) world

Expressed, for example, as predicate-argument relations (semantic roles)or modifiers in language



Propositions

While the media continues to spew emotionally charged tirades about how theanti-vaccination “movement” allegedly triggered the recent measles outbreak that healthauthorities believe started at Disneyland, actual science suggests that the most likely causeof this insanely overblown outbreak was a person who was recently vaccinated.

outbreak

measles

recent

Arg1

TMP



Propositions


outbreak

measles

recent

overblown Arg1insanely EXT



Propositions


triggered

outbreak

anti-vaccination movement

measles

recent

Arg1

Arg0

overblowninsanely



Propositions


triggered

outbreak

at Disneylandstarted


measles

recent

overblowninsanely

LOC

Arg0



Propositions


triggered

outbreak



measles

recent

causedArg1 personArg0overblowninsanely



Propositions


triggered

outbreak



measles

recent

caused person

vaccinated

recently

overblowninsanely

Arg1

TMP



Propositions


GRaSP model for linking mentions to instances (Fokkens & Vossen, thisafternoon)

triggered

outbreak



measles

recent

Arg1

TMP

Arg1

causedArg1 personArg0

vaccinated

recently

Arg0


LOC

Arg0 Arg1

TMP


Perspectives: attribution & factuality

Outline

1 Introduction




5 Future directions



Attribution & Factuality

These propositions are not necessarily the beliefs of the author→ attribution (Roser’s talk this morning)

Attitude of source (author or quoted) expressed towards proposition→ factuality (among many others)

Factuality1 is a combination of:

polarity (affirmative/negative)certainty (certain/probable/possible)

1R. Saurı and J. Pustejovsky. FactBank: A corpus annotated with event factuality. Language resources and evaluation, 43(3):227–268, 2009.





triggered

outbreak


Arg1

Arg0

AUTHORTHE MEDIA

AFFIRMATIVEPROBABLE

NEGATIVECERTAIN





outbreak

at Disneylandstarted LOC

Arg0

AUTHORHEALTH AUTHORITIES

AFFIRMATIVEPROBABLE

NEGATIVECERTAIN





outbreak causedArg1 personArg0

vaccinated

recently

Arg1

TMP

AUTHOR

ACTUAL SCIENCE

AFFIRMATIVEPROBABLE

NEGATIVECERTAIN

AFFIRMATIVEPROBABLE


Micro-propositions

Outline

1 Introduction




5 Future directions


Micro-propositions What are micro-propositions?

What are micro-propositions?


Propositions can be decomposed into micro-propositions

triggered

outbreak



measles

recent

Arg1

TMP

Arg1

causedArg1 personArg0

vaccinated

recently

Arg0


LOC

Arg0 Arg1

TMP


Micro-propositions Why do we need micro-propositions?

Why do we need micro-propositions?

Another example (taken from FactBank)

Two Libyans were suspected of blowing up a Pan Am jumbo jet overScotland in 1988.

two Libyans

blow_up

over ScotlandPan Am jumbo jet

in 1988

Arg0

Arg1

ArgM-TMP

ArgM-LOC






two Libyans

blow_up


in 1988

Arg0

Arg1

ArgM-TMP

ArgM-LOC

ARBITRARY SOURCE

AFFIRMATIVEPOSSIBLE






two Libyans

blow_up


in 1988

Arg0

Arg1

ArgM-TMP

ArgM-LOC

ARBITRARY SOURCE

AFFIRMATIVECERTAIN




We need to model perspectives (i.e. negation, modality, uncertainty,sentiment, etc.) at the level of micro-propositions

Allows for inference (e.g. implicit positive meaning)

“Vaccines do not cause autism in all children, obviously.”→ vaccines cause autism, but not in all children

“You cannot be vaccinated against malaria.”→ you can be vaccinated, but not against malaria“I don’t want to get the vaccination if it is not necessary.”→ I want to get the vaccination, but not if it is not necessary






“Vaccines do not cause autism in all children, obviously.”→ vaccines cause autism, but not in all children“You cannot be vaccinated against malaria.”→ you can be vaccinated, but not against malaria

“I don’t want to get the vaccination if it is not necessary.”→ I want to get the vaccination, but not if it is not necessary






“Vaccines do not cause autism in all children, obviously.”→ vaccines cause autism, but not in all children“You cannot be vaccinated against malaria.”→ you can be vaccinated, but not against malaria“I don’t want to get the vaccination if it is not necessary.”→ I want to get the vaccination, but not if it is not necessary



Back to our example


outbreak

at Disneylandstarted LOC

Arg0

AUTHORHEALTH AUTHORITIES

AFFIRMATIVEPROBABLE

NEGATIVECERTAIN



Another reason for micro-propositions


imagine acomplete text...

triggered

outbreak



measles

recent

caused person

vaccinated

recently

overblowninsanely

spew

tirades

the media

chargedemotionally






Some micro-propositions are more ‘important’ than others

Which (micro-)propositions contribute information that isold/presupposed?Which (micro-)propositions contribute new, non-derivable or contrastiveinformation that is of high communicative interest?


Future directions

Outline

1 Introduction




5 Future directions


Future directions

On-going work

Detecting implicit positive meaning from negated/modal statements(inference)

Detecting focus of statements (high communicative interest)

Annotation of these information layers in vaccination corpus

Representation in the GRaSP framework (see Antske’s talk)

Recognizing textual entailment (contradicting/confirming statements)


Future directions

Thank you for listening!

[email protected]


micro-propositions as a basis for deep text understanding...propositions can be decomposed...

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