95 research outputs found
Refining Implicit Argument Annotation for UCCA
Predicate-argument structure analysis is a central component in meaning
representations of text. The fact that some arguments are not explicitly
mentioned in a sentence gives rise to ambiguity in language understanding, and
renders it difficult for machines to interpret text correctly. However, only
few resources represent implicit roles for NLU, and existing studies in NLP
only make coarse distinctions between categories of arguments omitted from
linguistic form. This paper proposes a typology for fine-grained implicit
argument annotation on top of Universal Conceptual Cognitive Annotation's
foundational layer. The proposed implicit argument categorisation is driven by
theories of implicit role interpretation and consists of six types: Deictic,
Generic, Genre-based, Type-identifiable, Non-specific, and Iterated-set. We
exemplify our design by revisiting part of the UCCA EWT corpus, providing a new
dataset annotated with the refinement layer, and making a comparative analysis
with other schemes.Comment: DMR 202
Content Differences in Syntactic and Semantic Representations
Syntactic analysis plays an important role in semantic parsing, but the
nature of this role remains a topic of ongoing debate. The debate has been
constrained by the scarcity of empirical comparative studies between syntactic
and semantic schemes, which hinders the development of parsing methods informed
by the details of target schemes and constructions. We target this gap, and
take Universal Dependencies (UD) and UCCA as a test case. After abstracting
away from differences of convention or formalism, we find that most content
divergences can be ascribed to: (1) UCCA's distinction between a Scene and a
non-Scene; (2) UCCA's distinction between primary relations, secondary ones and
participants; (3) different treatment of multi-word expressions, and (4)
different treatment of inter-clause linkage. We further discuss the long tail
of cases where the two schemes take markedly different approaches. Finally, we
show that the proposed comparison methodology can be used for fine-grained
evaluation of UCCA parsing, highlighting both challenges and potential sources
for improvement. The substantial differences between the schemes suggest that
semantic parsers are likely to benefit downstream text understanding
applications beyond their syntactic counterparts.Comment: NAACL-HLT 2019 camera read
A Transition-Based Directed Acyclic Graph Parser for UCCA
We present the first parser for UCCA, a cross-linguistically applicable
framework for semantic representation, which builds on extensive typological
work and supports rapid annotation. UCCA poses a challenge for existing parsing
techniques, as it exhibits reentrancy (resulting in DAG structures),
discontinuous structures and non-terminal nodes corresponding to complex
semantic units. To our knowledge, the conjunction of these formal properties is
not supported by any existing parser. Our transition-based parser, which uses a
novel transition set and features based on bidirectional LSTMs, has value not
just for UCCA parsing: its ability to handle more general graph structures can
inform the development of parsers for other semantic DAG structures, and in
languages that frequently use discontinuous structures.Comment: 16 pages; Accepted as long paper at ACL201
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