A Corpus of Negations and their Underlying Positive Interpretations
25504Authors
nan
Abstract
AbstractNegation often conveys implicit positive meaning. In this paper, we present a corpus of negations and their underlying positive interpretations. We work with negations from Simple Wikipedia, automatically generate potential positive interpretations, and then collect manual annotations that effectively rewrite the negation in positive terms. This procedure yields positive interpretations for approximately 77% of negations, and the final corpus includes over 5,700 negations and over 5,900 positive interpretations. We also present baseline results using seq2seq neural models.
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Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM), pages 158–167 Minneapolis, June 6–7, 2019. c⃝2019 Association for Computational Linguistics 158 A Corpus of Negations and their Underlying Positive Interpretations Zahra Sarabi, Erin Killian, Eduardo Blanco and Alexis Palmer University of North Texas zahrasarabi@my.unt.edu, erinkillian@my.unt.edu, eduardo.blanco@unt.edu, alexis.palmer@unt.edu Abstract Negation often conveys implicit positive meaning. In this paper, we present a corpus of negations and their underlying positive in- terpretations. We work with negations from Simple Wikipedia, automatically generate po- tential positive interpretations, and then col- lect manual annotations that effectively rewrite the negation in positive terms. This proce- dure yields positive interpretations for approx- imately 77% of negations, and the final corpus includes over 5,700 negations and over 5,900 positive interpretations. We also present base- line results using seq2seq neural models. 1 Introduction Negation is present in every human language. It is in the first place a phenomenon of semantical opposition. As such, negation relates an expres- sion e to another expression with a meaning that is in some way opposed to the meaning of e (Horn and Wansing, 2015). Sentences containing nega- tion are generally (a) less informative than affir- mative ones (e.g., Milan is not the capital of Italy vs. Rome is the capital of Italy), (b) morphosyn- tactically more marked—all languages have neg- ative markers while only a few have affirmative markers, and (c) psychologically more complex and harder to process (Horn and Wansing, 2015). Negation often conveys implicit positive mean- ings (Rooth, 1992). This meaning ranges from im- plicatures to entailments, and we refer to it as pos- itive interpretations. Consider the following text from Simple Wikipedia:1 An abjad is an alpha- bet in which all its letters are consonants. Though vowels can be added in some abjads, they are not needed to write a word correctly. Some exam- ples of abjads are the Arabic alphabet and the 1https://simple.wikipedia.org/wiki/ Abjad 1 Mr. Smith apologized for :: not getting involved. Mr. Smith apologized for staying passive. 2 I :::: never heard of this guy before they started doing these commercials on television and radio. I heard of this guy after they started doing these com- mercials on on television and radio. 3 In Hinduism, beef is :: not allowed to be eaten. In Hinduism, chicken is allowed to be eaten. In other religions, beef is allowed to be eaten. Table 1: Three sentences containing a negation and their positive interpretations (italics). Hebrew alphabet. Humans intuitively understand that the negation (second sentence) implies the following positive interpretation: Though vowels can be added in some abjads, only consonants are needed to write a word correctly. Table 1 shows three sentences containing negation and their un- derlying positive interpretations. Positive interpre- tations do not have any negation cues (e.g., not, never) and Example 3 shows that some negations may have more than one underlying positive inter- pretation depending on the context. Revealing the underlying positive interpretation of negation is challenging. First, we need to iden- tify which …
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Labeled Text
AbstractNegation often conveys implicit positive meaning. In this paper, we present a corpus of negations and their underlying positive interpretations. We work with negations from Simple Wikipedia, automatically generate potential positive interpretations, and then collect manual annotations that effectively rewrite the negation in positive terms. This procedure yields positive interpretations for approximately 77% of negations, and the final corpus includes over 5,700 negations and over 5,900 positive interpretations. We also present baseline results using seq2seq neural models.
Publication Details
- Paper ID:
- 25504
- Year:
- 2019
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan