If No Media Were Allowed inside the Venue, Was Anybody Allowed?

Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 860–869, Valencia, Spain, April 3-7, 2017. c⃝2017 Association for Computational Linguistics If No Media Were Allowed inside the Venue, Was Anybody Allowed? Zahra Sarabi and Eduardo Blanco Human Intelligence and Language Technologies Lab University of North Texas Denton, TX, 76203 zahrasarabi@my.unt.edu, eduardo.blanco@unt.edu Abstract This paper presents a framework to under- stand negation in positive terms. Specif- ically, we extract positive meaning from negation when the negation cue syntacti- cally modifies a noun or adjective. Our approach is grounded on generating poten- tial positive interpretations automatically, and then scoring them. Experimental re- sults show that interpretations scored high can be reliably identified. 1 Introduction Negation is a complex phenomenon present in all human languages, allowing for the uniquely hu- man capacities of denial, contradiction, misrep- resentation, lying, and irony (Horn and Wans- ing, 2015). Acquiring and understanding negation poses unique challenges. For example, children acquire negation after learning to communicate in positive terms (Nordmeyer and Frank, 2013), and adults take longer to process sentences containing negation (Clark and Chase, 1972). In any given language, humans communicate in positive terms most of the time, and use negation to express something unusual or an ex- ception (Horn, 1989). But negation is ubiqui- tous (Morante and Sporleder, 2012): In scien- tific papers, 13.76% of sentences contain a nega- tion (Szarvas et al., 2008); in product reviews, 19% (Councill et al., 2010); and in Conan Doyle stories, 22.23% (Morante and Daelemans, 2012). From a theoretical perspective, it is accepted that negation has scope and focus, and that hu- mans intuitively understand positive meanings from negation (Rooth, 1992; Huddleston and Pul- lum, 2002). For example, from (1) John didn’t earn a steady paycheck until he was 40 years old, humans understand that (1a) John earned unsteady paychecks before he was 40 years old, and that (1b) John earned steady paychecks when he was 40 years old. This kind of positive interpretations would benefit language understanding in general. For example, a question answering system would benefit from interpretation (1b) when answering question Did John ever earn a steady paycheck? Within computational linguistics, automated approaches to extract positive meanings from negation target verbal negation (Section 3), i.e., when the negation cue is grammatically associ- ated with a verb, as in (1). Verbal negation ac- counts only for a portion of all negations, e.g., out of all syntactic dependencies indicating a negation modifier (neg dependency) in OntoNotes (Hovy et al., 2006), 64.4% modify verbs, 19.6% nouns, 10.3% adjectives, and 5.7% other part-of-speech tags. Non-verbal negation also conveys positive meanings, e.g., from (2) No media were allowed inside the venue (No modifies noun media), hu- mans understand that (2a) Somebody (e.g., invited guests) were allowed inside the venue and that (2b) Media where allowed somewhere outside the venue (presumably in a designated press area). Similarly, from (3) She was not alive when she got to the Lafayette area (not modifies …

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