@article {French:2001:0952-813X:421,
title = "Why co-occurrence information alone is not sufficient to answer subcognitive questions",
journal = "Journal of Experimental & Theoretical Artificial Intelligence",
parent_itemid = "infobike://tandf/teta",
publishercode ="tandf",
year = "2001",
volume = "13",
number = "4",
publication date ="2001-10-01T00:00:00",
pages = "421-429",
itemtype = "ARTICLE",
issn = "0952-813X",
eissn = "1362-3079",
url = "https://www.ingentaconnect.com/content/tandf/teta/2001/00000013/00000004/art00007",
doi = "doi:10.1080/09528130110104122",
keyword = "SUBCOGNITION, TURING TEST, SUBCOGNITIVE QUESTIONS, CONTEXT, CO-OCCURRENCE EMERGENCE, LARGE CORPORA",
author = "French, Robert M. and Labiouse, Christophe",
abstract = "Turney (2001) claims that a simple program, PMI-IR, that searches the World Wide Web for co-occurrences of words in 350 million Web pages can be used to find human-like answers to the type of 'subcognitive' questions French (1990) claimed would invariably unmask computers (that had not lived life as we humans had) in a Turing Test. This paper shows that there are serious problems with Turney's claim. We show that PMI-IR does not work for even simple subcognitive questions. PMI-IR's failure is attributed to its inability to understand the relational and contextual attributes of the words/concepts in the queries. Finally, it is shown that, even if PMI-IR were able to answer many subcognitive questions, a clever interrogator in the Turing Test would still be able to unmask the computer.",
}