3,461 research outputs found
Nightmare at test time: How punctuation prevents parsers from generalizing
Punctuation is a strong indicator of syntactic structure, and parsers trained
on text with punctuation often rely heavily on this signal. Punctuation is a
diversion, however, since human language processing does not rely on
punctuation to the same extent, and in informal texts, we therefore often leave
out punctuation. We also use punctuation ungrammatically for emphatic or
creative purposes, or simply by mistake. We show that (a) dependency parsers
are sensitive to both absence of punctuation and to alternative uses; (b)
neural parsers tend to be more sensitive than vintage parsers; (c) training
neural parsers without punctuation outperforms all out-of-the-box parsers
across all scenarios where punctuation departs from standard punctuation. Our
main experiments are on synthetically corrupted data to study the effect of
punctuation in isolation and avoid potential confounds, but we also show
effects on out-of-domain data.Comment: Analyzing and interpreting neural networks for NLP, EMNLP 2018
worksho
One model, two languages: training bilingual parsers with harmonized treebanks
We introduce an approach to train lexicalized parsers using bilingual corpora
obtained by merging harmonized treebanks of different languages, producing
parsers that can analyze sentences in either of the learned languages, or even
sentences that mix both. We test the approach on the Universal Dependency
Treebanks, training with MaltParser and MaltOptimizer. The results show that
these bilingual parsers are more than competitive, as most combinations not
only preserve accuracy, but some even achieve significant improvements over the
corresponding monolingual parsers. Preliminary experiments also show the
approach to be promising on texts with code-switching and when more languages
are added.Comment: 7 pages, 4 tables, 1 figur
DepAnn - An Annotation Tool for Dependency Treebanks
DepAnn is an interactive annotation tool for dependency treebanks, providing
both graphical and text-based annotation interfaces. The tool is aimed for
semi-automatic creation of treebanks. It aids the manual inspection and
correction of automatically created parses, making the annotation process
faster and less error-prone. A novel feature of the tool is that it enables the
user to view outputs from several parsers as the basis for creating the final
tree to be saved to the treebank. DepAnn uses TIGER-XML, an XML-based general
encoding format for both, representing the parser outputs and saving the
annotated treebank. The tool includes an automatic consistency checker for
sentence structures. In addition, the tool enables users to build structures
manually, add comments on the annotations, modify the tagsets, and mark
sentences for further revision
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
Experiences with the GTU grammar development environment
In this paper we describe our experiences with a tool for the development and
testing of natural language grammars called GTU (German:
Grammatik-Testumgebumg; grammar test environment). GTU supports four grammar
formalisms under a window-oriented user interface. Additionally, it contains a
set of German test sentences covering various syntactic phenomena as well as
three types of German lexicons that can be attached to a grammar via an
integrated lexicon interface. What follows is a description of the experiences
we gained when we used GTU as a tutoring tool for students and as an
experimental tool for CL researchers. From these we will derive the features
necessary for a future grammar workbench.Comment: 7 pages, uses aclap.st
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