Ben is an Applied Research Scientist at OpenStream.AI. Ben's dissertation, which he defended in 2024 under the supervision of Len Schubert, focused on the development of plan-based dialogue systems. He also contributed to a number of projects during his PhD, including MegaAttitude.
Kane, Benjamin, Will Gantt & Aaron Steven White. 2022. Intensional Gaps: Relating veridicality, factivity, doxasticity, bouleticity, and neg-raising. Semantics and Linguistic Theory 31. 570–605.
@article{kane_intensional_2022,
title = {Intensional {Gaps}: {Relating} veridicality, factivity, doxasticity, bouleticity, and neg-raising},
volume = {31},
copyright = {Copyright (c) 2022 Benjamin Kane, Will Gantt, Aaron Steven White},
issn = {2163-5951},
shorttitle = {Intensional {Gaps}},
url = {https://journals.linguisticsociety.org/proceedings/index.php/SALT/article/view/31.029},
doi = {10.3765/salt.v31i0.5137},
abstract = {We investigate which patterns of lexically triggered doxastic, bouletic, neg(ation)-raising, and veridicality inferences are (un)attested across clause-embedding verbs in English. To carry out this investigation, we use a multiview mixed effects mixture model to discover the inference patterns captured in three lexicon-scale inference judgment datasets: two existing datasets, MegaVeridicality and MegaNegRaising, which capture veridicality and neg-raising inferences across a wide swath of the English clause-embedding lexicon, and a new dataset, MegaIntensionality, which similarly captures doxastic and bouletic inferences. We focus in particular on inference patterns that are correlated with morphosyntactic distribution, as determined by how well those patterns predict the acceptability judgments in the MegaAcceptability dataset. We find that there are 15 such patterns attested. Similarities among these patterns suggest the possibility of underlying lexical semantic components that give rise to them. We use principal component analysis to discover these components and suggest generalizations that can be derived from them.},
language = {en},
urldate = {2022-01-13},
journal = {Semantics and Linguistic Theory},
author = {Kane, Benjamin and Gantt, Will and White, Aaron Steven},
month = jan,
year = {2022},
pages = {570--605},
}
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Gantt, William, Benjamin Kane & Aaron Steven White. 2020. Natural Language Inference with Mixed Effects. In Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics, 81–87. Barcelona, Spain (Online): Association for Computational Linguistics.
@inproceedings{gantt_natural_2020,
title = {Natural Language Inference with Mixed Effects},
author = {Gantt, William and
Kane, Benjamin and
White, Aaron Steven},
booktitle = {Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics},
month = dec,
year = {2020},
address = {Barcelona, Spain (Online)},
publisher = {Association for Computational Linguistics},
url = {https://www.aclweb.org/anthology/2020.starsem-1.9},
pages = {81--87}
}
