1,237 research outputs found
Connotation Frames: A Data-Driven Investigation
Through a particular choice of a predicate (e.g., "x violated y"), a writer
can subtly connote a range of implied sentiments and presupposed facts about
the entities x and y: (1) writer's perspective: projecting x as an
"antagonist"and y as a "victim", (2) entities' perspective: y probably dislikes
x, (3) effect: something bad happened to y, (4) value: y is something valuable,
and (5) mental state: y is distressed by the event. We introduce connotation
frames as a representation formalism to organize these rich dimensions of
connotation using typed relations. First, we investigate the feasibility of
obtaining connotative labels through crowdsourcing experiments. We then present
models for predicting the connotation frames of verb predicates based on their
distributional word representations and the interplay between different types
of connotative relations. Empirical results confirm that connotation frames can
be induced from various data sources that reflect how people use language and
give rise to the connotative meanings. We conclude with analytical results that
show the potential use of connotation frames for analyzing subtle biases in
online news media.Comment: 11 pages, published in Proceedings of ACL 201
Editorial : acquisition of clause chaining
Research on the acquisition of complex syntax has largely overlooked a special type of complex sentence, found in hundreds of languages outside Western Europe: the clause chain. A clause chain contains as few as one and as many as 20 or more “medial” clauses, with verbal predicates that are under-specified for tense and other categories, and a single “final” (finite) clause, with a verbal predicate that is fully-specified for tense and, often, other categories. “Medial” clauses relate syntactically to other clauses in the chain without being subordinated to them. In some languages,
each clause in a chain must indicate in advance whether the subject of the next clause will be the same as or different from that of the current clause, through “switch-reference” marking (Haiman and Munro, 1983; van Gijn and Hammond, 2016). Unlike English complex sentences, clause chains’
distribution is partially predictable in that it is often associated with description of temporally sequential events or actions
ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning
We present ATOMIC, an atlas of everyday commonsense reasoning, organized
through 877k textual descriptions of inferential knowledge. Compared to
existing resources that center around taxonomic knowledge, ATOMIC focuses on
inferential knowledge organized as typed if-then relations with variables
(e.g., "if X pays Y a compliment, then Y will likely return the compliment").
We propose nine if-then relation types to distinguish causes vs. effects,
agents vs. themes, voluntary vs. involuntary events, and actions vs. mental
states. By generatively training on the rich inferential knowledge described in
ATOMIC, we show that neural models can acquire simple commonsense capabilities
and reason about previously unseen events. Experimental results demonstrate
that multitask models that incorporate the hierarchical structure of if-then
relation types lead to more accurate inference compared to models trained in
isolation, as measured by both automatic and human evaluation.Comment: AAAI 2019 C
Towards Transparent, Reusable, and Customizable Data Science in Computational Notebooks
Data science workflows are human-centered processes involving on-demand
programming and analysis. While programmable and interactive interfaces such as
widgets embedded within computational notebooks are suitable for these
workflows, they lack robust state management capabilities and do not support
user-defined customization of the interactive components. The absence of such
capabilities hinders workflow reusability and transparency while limiting the
scope of exploration of the end-users. In response, we developed MAGNETON, a
framework for authoring interactive widgets within computational notebooks that
enables transparent, reusable, and customizable data science workflows. The
framework enhances existing widgets to support fine-grained interaction history
management, reusable states, and user-defined customizations. We conducted
three case studies in a real-world knowledge graph construction and serving
platform to evaluate the effectiveness of these widgets. Based on the
observations, we discuss future implications of employing MAGNETON widgets for
general-purpose data science workflows.Comment: To appear at Extended Abstracts of the 2023 CHI Conference on Human
Factors in Computing System
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