Other dataset for training

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최홍석

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Nov 28, 2018, 11:40:54 PM11/28/18
to SemEval 2019: Task 9

Dear task organizers.

I have a quick question.

I read the terms of the submitted systems as below.
"Teams should not use manually labeled training dataset (suggestion labeled sentences) outside the one provided as a part of this competition."

Does it mean that it is possible to use dataset labeled by other label? such as positive, negative ... . (not suggestion/non-suggestion)

Thanks in advance.

Best regards.

HongSeok Choi.


Sapna Negi

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Nov 29, 2018, 8:57:53 AM11/29/18
to 최홍석, SemEval 2019: Task 9
Hi HongSeok Choi


What we mean in that rule is that the additional data should not be a manually labeled dataset where labels mean that a suggestion is present/absent in the sentence.

If the additional dataset contains labels which indicate some other information (eg sentiments), that should be fine.

Let us know if this is what you mean to ask.

Regards
Sapna

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최홍석

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Nov 29, 2018, 10:08:31 AM11/29/18
to SemEval 2019: Task 9

Yeah!, your answer is exactly what I mean to ask.

Really thanks for your answering my question.

Best regards.

HongSeok Choi


2018년 11월 29일 목요일 오후 10시 57분 53초 UTC+9, Sapna Negi 님의 말:
Hi HongSeok Choi


What we mean in that rule is that the additional data should not be a manually labeled dataset where labels mean that a suggestion is present/absent in the sentence.

If the additional dataset contains labels which indicate some other information (eg sentiments), that should be fine.

Let us know if this is what you mean to ask.

Regards
Sapna

On 29 Nov 2018, at 04:40, 최홍석 <hongk...@gmail.com> wrote:


Dear task organizers.

I have a quick question.

I read the terms of the submitted systems as below.
"Teams should not use manually labeled training dataset (suggestion labeled sentences) outside the one provided as a part of this competition."

Does it mean that it is possible to use dataset labeled by other label? such as positive, negative ... . (not suggestion/non-suggestion)

Thanks in advance.

Best regards.

HongSeok Choi.



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