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locks; strict;
comment	@# @;


1.4
date	2021.10.26.11.21.28;	author nia;	state Exp;
branches;
next	1.3;
commitid	TS3y6sgAeGKWpjeD;

1.3
date	2021.10.07.15.00.34;	author nia;	state Exp;
branches;
next	1.2;
commitid	0fS32tEWoNe7fTbD;

1.2
date	2015.11.04.01.59.17;	author agc;	state Exp;
branches;
next	1.1;
commitid	8Vi0UoG7obKytIHy;

1.1
date	2013.05.22.13.07.47;	author obache;	state Exp;
branches;
next	;
commitid	iYNWviKUftNLYCQw;


desc
@@


1.4
log
@textproc: Replace RMD160 checksums with BLAKE2s checksums

All checksums have been double-checked against existing RMD160 and
SHA512 hashes

Unfetchable distfiles (fetched conditionally?):
./textproc/convertlit/distinfo clit18src.zip
@
text
@$NetBSD: distinfo,v 1.3 2021/10/07 15:00:34 nia Exp $

BLAKE2s (CRF++-0.58.tar.gz) = 0f57982540c36c2f00fbc6fd42a1f7c1f15bf0b425d62dc440e3a459f6ce04a9
SHA512 (CRF++-0.58.tar.gz) = 676b3e9ed89b5fb2f246175b58c384f10cab09fff8329c07311fed3832f55dbad26a25d2946c9efaa75cd8026517cb9e1742bb70ca26187367747852073e4eb9
Size (CRF++-0.58.tar.gz) = 790570 bytes
SHA1 (patch-configure) = 5a8a098fff9eaeed841b6de3d2719fc6193764ef
@


1.3
log
@textproc: Remove SHA1 hashes for distfiles
@
text
@d1 1
a1 1
$NetBSD: distinfo,v 1.2 2015/11/04 01:59:17 agc Exp $
d3 1
a3 1
RMD160 (CRF++-0.58.tar.gz) = 3c70d129f06d88e13ece94d505dd417668f0a7bc
@


1.2
log
@Add SHA512 digests for distfiles for textproc category

Problems found locating distfiles:
	Package cabocha: missing distfile cabocha-0.68.tar.bz2
	Package convertlit: missing distfile clit18src.zip
	Package php-enchant: missing distfile php-enchant/enchant-1.1.0.tgz

Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden).  All existing
SHA1 digests retained for now as an audit trail.
@
text
@d1 1
a1 1
$NetBSD: distinfo,v 1.1 2013/05/22 13:07:47 obache Exp $
a2 1
SHA1 (CRF++-0.58.tar.gz) = 979a686a6d73d14cdd0c96a310888fb6bffd2e91
@


1.1
log
@Import CRF++-0.58 as textproc/CRF++.

CRF++ is a simple, customizable, and open source implementation of Conditional
Random Fields (CRFs) for segmenting/labeling sequential data. CRF++ is designed
for generic purpose and will be applied to a variety of NLP tasks, such as Named
Entity Recognition, Information Extraction and Text Chunking.
@
text
@d1 1
a1 1
$NetBSD$
d5 1
@