‘The Michael Jordan of greatness’—Extracting Vossian antonomasia from two decades ofThe New York Times, 1987–2007

Abstract

Vossian Antonomasia is a prolific stylistic device, in use since antiquity. It can compress the introduction or description of a person or another named entity into a terse, poignant formulation and can best be explained by an example: When Norwegian world champion Magnus Carlsen is described as "the Mozart of chess", it is Vossian Antonomasia we are dealing with. The pattern is simple: A source (Mozart) is used to describe a target (Magnus Carlsen), the transfer of meaning is reached via a modifier ("of chess"). This phenomenon has been discussed before (as 'metaphorical antonomasia' or, with special focus on the source object, as 'paragons'), but no corpusbased approach has been undertaken as yet to explore its breadth and variety. We are looking into a full-text newspaper corpus (The New York Times, 1987-2007 and describe a new method for the automatic extraction of Vossian Antonomasia based on Wikidata entities. Our analysis offers new insights into the occurrence of popular paragons and their distribution.

“The Rodney Dangerfield of Stylistic Devices”: End-to-End Detection and Extraction of Vossian Antonomasia Using Neural Networks

“…A second semi-automatic approach was proposed by Fischer and Jäschke ( 2019 ), who focused on the pattern “the ENTITY of”. As a first step, they used regular expressions to extract only the candidate sentences with the mentioned pattern.…”

“…After using Wikidata for distant supervision linking all candidates to Wikidata “human” entities, they manually created a list to exclude common false positive candidates like “the House of” or “the Prince of”, as those names matched Wikidata entities. Schwab et al ( 2019 ) presented the first fully automated approach by extending the idea of Fischer and Jäschke ( 2019 ). They introduced three different methods.…”

“A Buster Keaton of Linguistics”: First Automated Approaches for the Extraction of Vossian Antonomasia

“…(Cohen et al, 2015). The only attempt automating the extraction has been presented by Fischer and Jäschke (2019). Their semi-automatic approach for English texts extracts VA candidates for only one single pattern, the EN-TITY of.…”

“…Using the New York Times corpus (Sandhaus, 2008) Using Wikidata for distant supervision, we keep only candidates whose string matches the exact name or alias of Wikidata entities, respecting the case of letters, with 'instance-of' property 'human', and exclude candidates using the manually curated blacklist 5 provided by Fischer and Jäschke (2019). 6 We consider this procedure of "regex -Wikidata -blacklist" as baseline.…”

“…In our evaluation, we compare them against a baseline and assess the difficulty of identifying VAs using crowdsourcing. In addition, we extend the only existing larger data set (Fischer and Jäschke, 2019) with VAs of eight additional patterns. We have also double-checked and corrected existing and new annotations.…”