Welcome to Etherpad!

This pad text is synchronized as you type, so that everyone viewing this page sees the same text. This allows you to collaborate seamlessly on documents!

Get involved with Etherpad at http://etherpad.org Notes : Modality and Negation: An Introduction to the Special Issue (2012)
by Roser Morante, University of Antwerp & Caroline Sporleder, Saarland University
  http://www.anthology.aclweb.org/J/J12/J12-2001.pdf
 
“Certainty”? & “Modality”?


Traditionally, most research in NLP has focused on propositional aspects of meaning. To truly understand language, however, extra-propositional aspects are equally important. Modality and negation typically contribute significantly to these extra-propositional meaning aspects.

Researchers have started to work on modeling factuality, belief and certainty, detecting speculative sentences and hedging, identifying contradictions, and determining the scope of expressions of modality and negation. 

In this article, we will provide an overview of how modality and negation have been modeled in computational linguistics.

1. introduction

grammatical phenomena

One of the first categorizations of modality is proposed by Otto Jespersen (1924 = The Philosophy of Grammer) in the chapter about Mood, where the grammarian distinguishes between “categories containing an element of will” and categories “containing no element of will.”


extra-propositional meanings to the event LAY OFF(GM,workers):

Generally speaking, modality is a grammatical category that allows the expression of aspects related to the attitude of the speaker towards her statements in terms of degree of certainty, reliability, subjectivity, sources of information, and perspective. We understand modality in a broad sense, which involves related concepts like “subjectivity”, “hedging”, “evidentiality”, “uncertainty”, “committed belief,” and “factuality”.

So far computational linguistics addressed these two main tasks:  

Modality recognition is used for:  

Most of the work in this area has been carried out at the sentence or predicate level.  

2. Modality

From a theoretical perspective, modality can be defined as:


...modality is a big intrigue.Questions erstwhile considered solved become open questions again. New observations and hypotheses come to light, not least because the subject matter is changing.
(Salkie, Busuttil, and van der Auwera (2009, page 7))

To mention some examples, research focuses on 
These concepts are related to the attitude of the speaker towards her statements in terms of degree of

Theoretical linguistic background of 'modality':



Additionally, Palmer indicates other categories that may be marked as irrealis and may be found in the mood system: 

Fintel (2006), philosophic modality is a category that deals with

The term hedging is originally due to Lakoff (1972, page 195), who describes hedges as “words whose job is to make things more or less fuzzy.”(...) Lakoff starts from the observation that “natural language concepts have vague boundaries and fuzzy edges and that, consequently, natural language sentences will very often be neither true, nor false, nor nonsensical, but rather true to a certain extent and false to a certain extent, true in certain aspects and false in certain aspects” (Lakoff 1972, page 183) In order to deal with this aspect of language, he extends the classical propositional and predicate logic to fuzzy logic and focuses on the study of hedges. (227)

Hyland (1998) studies hedging in scientific texts.  
He proposes a pragmatic classification of hedge expressions based on an exhaustive analysis of a corpus. The catalogue of hedging cues includes modal auxiliaries, epistemic lexical verbs, epistemic adjectives, adverbs, nouns, and a variety of non-lexical cues.

Certainty is a type of subjective information that can be conceived of as a variety of epistemic modality (Rubin, Liddy, and Kando 2005). Here we take their definition (page 65):
. . . certainty is viewed as a type of subjective information available in texts and a form of epistemic modality expressed through explicitly-coded linguistic means (what are linguistic means?) . Such devices [...] explicitly signal presence of certainty information that covers a full continuum of writer’s confidence, ranging from uncertain possibility and withholding full commitment to statements.

Modality and evidentiality are grammatical categories
whereas certainty, hedging, and subjectivity are pragmatic positions
and event factuality is a level of information . (228)

Modality-related phenomena are not rare. 


4. Categorizing and Annotating Modality and Negation

categorization schemes
annotated corpora

'modality attributes':

OntoSem project 
( Nirenburg and Raskin 2004):
modality type
value
scope
attributed-to

(9) Entrance to the tower should be totally camouflaged
In Example (9), should is identified as a modality cue and characterized with :

MPQA Opinion Corpus
(Wiebe, Wilson, and Cardie 2005)
10,657 sentences in 535 documents of English newswire
private state frames
properties

Automatic Content Extraction 2008 corpus (Linguistic Data Consortium 2008)
 English and Arabic texts from a variety of resources including radio and TV broadcast news, talk shows, newswire articles, Internet news groups, Web logs, and conversational telephone speech

TimeML
(Pustejovsky et al, 2005)
language for events and temporal expressions, used for TimeBank
Situation Selecting Predicates (SSPs):

FactBank:
(Saur ?? and Pustejovsky 2009)
a corpus of events annotated with factuality information, by using the Square of Opposition (Aristotle)
degree of factualities:

--> but in the paper there is another set of categories

modality lexicon 
(Baker et al., 2010)
http://www.umiacs.umd.edu/~bonnie/ModalityLexicon.txt
to automatically annotate a corpus with modality information
the lexicon entries structure:
three components are identified in a sentence:
eight modalities:

The annotation work by Wilbur, Rzhetsky, and Shatkay (2006) is motivated by the need to identify and characterize parts of scientific documents where reliable information can be found. 
They define five dimensions to characterize scientific sentences: 

Scientific language makes use of speculation and hedging to express lack of definite belief


5. Detection of Speculative Sentences

Three types of text analysis seem to be able to detect speculation:
From the research presented in this section it seems that classifying sentences as to whether they are speculative or not can be performed by using knowledge-poor machine learning approaches as well as by linguistically motivated methods.It has also been shown that it is feasible to build a hedge classifier in an unsupervised manner. (241)


10. Final Remarks

which aspects of extra-propositional meaning need to be modeled for which applications. Outside sentiment analysis, relatively little research has been carried out in this area so far.

most research so far has been carried out on English and on selected domains and genres (biomedical, reviews, newswire).

It would also be good to broaden the set of domains and genres (including fiction, scientific texts, weblogs, etc.) since extra-propositional meaning is particularly susceptible to domain and genre effects.