Models based on the transformer architecture, such as BERT, have marked a crucial step forward in the field of Natural Language Processing. Importantly, they allow the creation of word embeddings that capture important semantic information about word
s in context. However, as single entities, these embeddings are difficult to interpret and the models used to create them have been described as opaque. Binder and colleagues proposed an intuitive embedding space where each dimension is based on one of 65 core semantic features. Unfortunately, the space only exists for a small data-set of 535 words, limiting its uses. Previous work (Utsumi, 2018, 2020; Turton et al., 2020) has shown that Binder features can be derived from static embeddings and successfully extrapolated to a large new vocabulary. Taking the next step, this paper demonstrates that Binder features can be derived from the BERT embedding space. This provides two things; (1) semantic feature values derived from contextualised word embeddings and (2) insights into how semantic features are represented across the different layers of the BERT model.
We present a method for computing all quantifer scopes that can be extracted from a single CCG derivation. To do that we build on the proposal of Steedman (1999, 2011) where all existential quantifiers are treated as Skolem functions. We extend the a
pproach by introducing a better packed representation of all possible specifications that also includes node addresses where the specifications happen. These addresses are necessary for recovering all, and only, possible readings.
Formaldehyde is classified by the World Health Organization (International Agency
for Research on Cancer) as a carcinogen in Group 1. The upper limit allowed for use in
cosmetic products as a preservative has to not exceed 0.2%. This study aims to
detect and
determine formaldehyde level in some cosmetic products available in the local market
using acetyl acetone method. Formaldehyde was detected in 77% of the studied cosmetic
products (49 samples) despite the fact that most of them were not labeled formaldehyde or
formaldehyde donor preservatives (about 70%). The amount of formaldehyde in keratin
samples were higher than the allowed limit (0.34% -11.73%) except one sample 0.18%. pH
decrease and temperature increase of keratin samples led to an increase of formaldehyde
level as a result of its release from preservatives.
We study in this research completeness problem in three valued algebraic logic on Lukasiewicz 3 valued logic for a functionally complete set of connectives where we studied this problem in Wajseberg derivation system and we presented a comprehensive
study of the most important theorems and derivation rules which led to a very unique and special proof of completeness theorem in Lukasiewicz 3 valued logic.
