Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Weakly Supervised Cross-Lingual Named Entity Recognition via Effective
  Annotation and Representation Projection   The state-of-the-art named entity recognition (NER) systems are supervised
machine learning models that require large amounts of manually annotated data
to achieve high accuracy. However, annotating NER data by human is expensive
and time-consuming, and can be quite difficult for a new language. In this
paper, we present two weakly supervised approaches for cross-lingual NER with
no human annotation in a target language. The first approach is to create
automatically labeled NER data for a target language via annotation projection
on comparable corpora, where we develop a heuristic scheme that effectively
selects good-quality projection-labeled data from noisy data. The second
approach is to project distributed representations of words (word embeddings)
from a target language to a source language, so that the source-language NER
system can be applied to the target language without re-training. We also
design two co-decoding schemes that effectively combine the outputs of the two
projection-based approaches. We evaluate the performance of the proposed
approaches on both in-house and open NER data for several target languages. The
results show that the combined systems outperform three other weakly supervised
approaches on the CoNLL data.

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The categories of this paper are: comp-gas
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The categories of this paper are: nucl-th
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The categories of this paper are: patt-sol
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The categories of this paper are: math-ph
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The categories of this paper are: q-fin
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The categories of this paper are: dg-ga
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The categories of this paper are: mtrl-th
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The categories of this paper are: stat
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The categories of this paper are: ao-sci
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The categories of this paper are: q-bio
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The categories of this paper are: alg-geom
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The categories of this paper are: math
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The categories of this paper are: solv-int
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The categories of this paper are: physics
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The categories of this paper are: q-alg
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The categories of this paper are: acc-phys