tech,13-2-P03-1030,bq |
detection
</term>
as
<term>
information retrieval
|
task
|
</term>
and hypothesize on the impact of
<term>
|
#4078
In this paper we formulate story link detection and new event detection as information retrieval task and hypothesize on the impact of precision and recall on both systems. |
|
the
<term>
text
</term>
is irrelevant to the
|
task
|
. The
<term>
parser
</term>
gains algorithmic
|
#17585
We present an efficient algorithm for chart-based phrase structure parsing of natural language that is tailored to the problem of extracting specific information from unrestricted texts where many of the words are unknown and much of the text is irrelevant to the task. |
|
larger volume from the
<term>
Web
</term>
. The
|
task
|
of
<term>
machine translation ( MT ) evaluation
|
#8317
The task of machine translation (MT) evaluation is closely related to the task of sentence-level semantic equivalence classification. |
other,9-5-P05-1067,bq |
model
</term>
for the
<term>
machine translation
|
task
|
</term>
, which can also be viewed as a
<term>
|
#9485
Second, we describe the graphical model for the machine translation task, which can also be viewed as a stochastic tree-to-tree transducer. |
other,21-1-C88-2130,bq |
or house , a much-studied
<term>
discourse
|
task
|
</term>
first characterized linguistically
|
#15456
We have developed a computational model of the process of describing the layout of an apartment or house, a much-studied discourse task first characterized linguistically by Linde (1974). |
tech,14-5-P05-1069,bq |
standard
<term>
Arabic-English translation
|
task
|
</term>
. Previous work has used
<term>
monolingual
|
#9652
The best system obtains a 18.6% improvement over the baseline on a standard Arabic-English translation task. |
|
<term>
paraphrases
</term>
. We show that this
|
task
|
can be done using
<term>
bilingual parallel
|
#9671
We show that this task can be done using bilingual parallel corpora, a much more commonly available resource. |
|
procedure
</term>
is proposed to deal with the
|
task
|
of
<term>
syntactic ambiguity resolution
</term>
|
#17815
In this paper, a discrimination and robustness oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. |
|
<term>
syntax
</term>
, for instance , to the
|
task
|
of
<term>
semantic interpretation
</term>
or
|
#16454
The unique properties of tree-adjoining grammars (TAG) present a challenge for the application of TAGs beyond the limited confines of syntax, for instance, to the task of semantic interpretation or automatic translation of natural language. |
|
topic signatures
</term>
on a
<term>
WSD
</term>
|
task
|
, where we trained a
<term>
second-order
|
#7002
We evaluated the topic signatures on a WSDtask, where we trained a second-order vector co-occurrence algorithm on standard WSD datasets, with promising results. |
|
time finding more data relevant to their
|
task
|
, and gives them translingual reach into
|
#3619
It gives users the ability to spend their time finding more data relevant to their task, and gives them translingual reach into other languages by leveraging human language technology. |
tech,14-4-P80-1004,bq |
reconstruction
</term>
to a
<term>
recognition
|
task
|
</term>
. Implications towards automating
|
#12513
It is argued that the method reduces metaphor interpretation from a reconstruction to a recognition task. |
|
for such a
<term>
need
</term>
is a valuable
|
task
|
. We investigate that claim by adopting
|
#10760
Finding the preferred language for such a need is a valuable task. |
tech,27-2-N03-2003,bq |
topic
</term>
of the target
<term>
recognition
|
task
|
</term>
, but also that it is possible to
|
#3056
In this paper, we show how training data can be supplemented with text from the web filtered to match the style and/or topic of the target recognition task, but also that it is possible to get bigger performance gains from the data by using class-dependent interpolation of N-grams. |
|
human judges
</term>
. We reconceptualize the
|
task
|
into two distinct phases . First , a very
|
#1368
We reconceptualize the task into two distinct phases. |
|
forming an
<term>
utterance
</term>
about a
|
task
|
and in determining the conversational vehicle
|
#14558
We want to illustrate a framework less restrictive than earlier ones by allowing a speaker leeway in forming an utterance about a task and in determining the conversational vehicle to deliver it. |
|
organized in a
<term>
hierarchy
</term>
; this
|
task
|
was discussed in previous papers [ Zernik87
|
#15858
First, how linguistic concepts are acquired from training examples and organized in a hierarchy; this task was discussed in previous papers [Zernik87]. |
|
indicators for the top-level prediction
|
task
|
. We also find that the
<term>
transcription
|
#10606
Examination of the effect of features shows that predicting top-level and predicting subtopic boundaries are two distinct tasks: (1) for predicting subtopic boundaries, the lexical cohesion-based approach alone can achieve competitive results, (2) for predicting top-level boundaries, the machine learning approach that combines lexical-cohesion and conversational features performs best, and (3) conversational cues, such as cue phrases and overlapping speech, are better indicators for the top-level prediction task. |
|
Annotating
<term>
honorifics
</term>
is a complex
|
task
|
that involves identifying a
<term>
predicate
|
#8621
Annotating honorifics is a complex task that involves identifying a predicate with honorifics, assigning ranks to referents of the predicate, calibrating the ranks, and connecting referents with their predicates. |
other,10-4-N04-1022,bq |
on a
<term>
Chinese-to-English translation
|
task
|
</term>
. Our results show that
<term>
MBR
|
#6624
We report the performance of the MBR decoders on a Chinese-to-English translation task. |