BibTeX
@InProceedings{boleda17:_instan_concep_distr_space,
abstract = {Instances (``Mozart'') are ontologically distinct from
concepts or classes (``composer''). Natural language
encompasses both, but instances have received
comparatively little attention in distributional
semantics. Our results show that instances and
concepts differ in their distributional
properties. We also establish that instantiation
detection (``Mozart -- composer'') is generally
easier than hypernymy detection (``chemist --
scientist''), and that results on the influence of
input representation do not transfer from hyponymy
to instantiation.},
address = {Valencia, Spain},
author = {Boleda, Gemma and Gupta, Abhijeet and Pad{o}, Sebastian},
booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics},
interhash = {4fccc5bec96863e48b0aa1efc00cf904},
intrahash = {572c75d2a71ba7d51970dc1256c905e3},
month = {April},
pages = {79-85},
title = {Instances and concepts in distributional space},
url = {https://www.aclweb.org/anthology/E17-2013.pdf},
year = 2017
}
@InProceedings{gupta15:_distr,
author = {Abhijeet Gupta and Gemma Boleda and Marco Baroni and Sebastian Pad{ó}},
title = {Distributional vectors encode referential attributes},
booktitle = {Proceedings of EMNLP},
year = {2015},
address = {Lisbon, Portugal},
url = {https://www.aclweb.org/anthology/D/D15/D15-1002}
}
@InProceedings{abhijeet15:_mappin,
author = {Abhijeet Gupta and Gemma Boleda and Marco Baroni and Sebastian Pad{ó}},
title = {Mapping conceptual features to referential properties},
booktitle = {Procedings of the 3rd international {ESSENCE} workshop: Algorithms
for processing meaning},
year = {2015},
address = {Barcelona, Spain}
}
@InProceedings{gupta17:_distr_predic_relat_entit,
author = {Abhijeet Gupta and Gemma Boleda and Sebastian Padó},
title = {Distributed Prediction of Relations for Entities: The Easy, The Difficult, and The Impossible},
booktitle = {Proceedings of STARSEM},
keywords = {conference myown},
year = 2017,
address = {Vancouver, BC},
pages = {104-109},
note = {Acceptance rate: 36 url = {https://www.aclweb.org/anthology/S17-1012.pdf}}
@InProceedings{gupta15:_dissec_pract_lexic_funct_model,
author = {Abhijeet Gupta and Jason Utt and Sebastian Pad{ó}},
title = {Dissecting the Practical Lexical Function Model for Compositional
Distributional Semantics},
booktitle = {Proceedings of STARSEM},
year = {2015},
pages = {153-158},
address = {Denver, CO},
url = {https://www.aclweb.org/anthology/S15-1017}
}
@InProceedings{thejas19:_text_joint_predic_numer_categ,
address = {Varna, Bulgaria},
author = {Thejas, V and Gupta, Abhijeet and Pad{o}, Sebastian},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2be9c6dd7d7ff0156cce6ef67f34efb60/sp},
booktitle = {Proceedings of RANLP},
interhash = {aadafde536a389261411024934d94b82},
intrahash = {be9c6dd7d7ff0156cce6ef67f34efb60},
keywords = {sys:relevantfor:tcl-ims conference myown},
timestamp = {2019-10-17T17:40:19.000+0200},
title = {Text-based Joint Prediction of Numeric and Categorical Attributes of Entities in Knowledge Bases},
year = 2019
}
@article{westera:_word,
abstract = { Cognitive scientists have long used distributional semantic
representations of categories. The predominant approach uses
distributional representations of category-denoting nouns, like
"city" for the category city. We propose a novel scheme that
represents categories as prototypes over representations of
textit {names} of its members, such as "Barcelona", "Mumbai",
and "Wuhan" for the category city. This name-based representation
empirically outperforms the noun-based representation on two
experiments (modelling human judgments of category relatedness and
predicting category membership) with particular improvements for
ambiguous nouns. We discuss the model complexity of both classes of
models and argue that the name-based model has superior explanatory
potential with regard to concept acquisition.},
added-at = {2021-07-09T11:27:40.000+0200},
author = {Westera, Matthijs and Gupta, Abhijeet and Boleda, Gemma and Padó, Sebastian},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2e7dc0d19377b7de5c332f392f55fe283/sp},
interhash = {2672b0d253e761282b859ae438a6277e},
intrahash = {e7dc0d19377b7de5c332f392f55fe283},
journal = {Cognitive Science},
keywords = {article myown},
number = 9,
pages = {e13029},
timestamp = {2021-09-07T16:13:44.000+0200},
title = {Distributional models of category concepts based on names of category members},
url = {https://doi.org/10.1111/cogs.13029},
volume = 45,
year = 2021
}