Converts between KorAP-XML ZIP format and formats like CoNLL-U, Krill, word2vec, NOW and annotates KorAP XML ZIPs with various taggers and parsers.
Drop-in replacement for korapxml2conllu, conllu2korapxml (see KorAP-XML-CoNLL-U) and korapxml2krill (see KorAP-XML-Krill), but still in the experimental stage. This concerns in particular the command line options, which might not yet be fully tested in all combinations.
This tool is designed to be run on a Unix-like system (e.g., Linux, macOS).
- Java 21 or higher is required.
In addition to Java 21, the following are required for the wrapper scripts:
- A Unix-like environment with a
bashshell. - The
statcommand-line utility. - For automatic memory detection, the system needs to support cgroups, specifically
/sys/fs/cgroup/memory.
./gradlew buildAfter building, a fat jar file will be available at ./app/build/libs/korapxmltool.jar. In addition,
the executable korapxmltool, as well as the symbolic link shortcuts korapxml2conllu and korapxml2krill, will
be available at ./build/bin/.
Key options for korapxmltool (>= v3.1):
-t FORMAT,--to FORMAT: Output format (zip,conllu,w2v,now,krill)-j N,--jobs N,--threads N: Number of threads/jobs to use--zip-parallelism N: Maximum ZIP files read concurrently (default: up to 8); XML entry work still uses--threads--largest-first: Schedule larger input ZIPs first (opt-in; the default is argument order)-T TAGGER[:MODEL],--tag-with TAGGER[:MODEL]: POS tagger and optional model-P PARSER[:MODEL],--parse-with PARSER[:MODEL]: Parser and optional model-f,--force: Overwrite existing output files-q,--quiet: Suppress progress output-D DIR,--output-dir DIR: Output directory-L DIR,--log-dir DIR: Log directory--lemma: Use lemmas instead of surface forms (when available)--lemma-only: Skip loading base tokens, output only lemmas
For the wrapper scripts in build/bin/, you can configure the JVM and model paths via environment variables:
KORAPXMLTOOL_MODELS_PATH: Directory where tagger and parser models are searched if not found locally. (Default:../lib/modelsrelative to the wrapper script's directory)KORAPXMLTOOL_XMX: Maximum Java heap memory size (e.g.,16g,500g). (Default: auto-detected based on available system memory, input size, and workload type)KORAPXMLTOOL_JAVA_OPTS: Additional Java options (e.g.,-XX:+UseG1GC).
Conversion to CoNLL-U format
$ ./build/bin/korapxmltool app/src/test/resources/wdf19.zip | head -10
# foundry = base
# filename = WDF19/A0000/13072/base/tokens.xml
# text_id = WDF19_A0000.13072
# start_offsets = 0 0 14 17 25 30 35 42 44 52 60 73
# end_offsets = 74 12 16 24 29 34 41 43 51 59 72 74
1 Australasien _ _ _ _ _ _ _ _
2 on _ _ _ _ _ _ _ _
3 devrait _ _ _ _ _ _ _ _
4 peut _ _ _ _ _ _ _ _
5 ĂȘtre _ _ _ _ _ _ _ _
$ ./build/bin/korapxmltool -t w2v app/src/test/resources//wdf19.zip
Arts visuels Pourquoi toujours vouloir séparer BD et Manga ?
Ffx 18:20 fév 25 , 2003 ( CET ) soit on ne sépara pas , soit alors on distingue aussi , le comics , le manwa , le manga ..
la bd belge et touts les auteurs européens ..
on commence aussi a parlé de la bd africaine et donc ...
wikipedia ce prete parfaitement Ă ce genre de decryptage .
âŠ./build/bin/korapxmltool -m '<textSigle>([^<]+)' -m '<creatDate>([^<]+)' -t w2v app/src/test/resources//wdf19.zipWDF19/A0000.10894 2014.08.28 Arts visuels Pourquoi toujours vouloir sĂ©parer BD et Manga ?
WDF19/A0000.10894 2014.08.28 Ffx 18:20 fév 25 , 2003 ( CET ) soit on ne sépara pas , soit alors on distingue aussi , le comics , le manwa , le manga ..
WDF19/A0000.10894 2014.08.28 la bd belge et touts les auteurs européens ..
WDF19/A0000.10894 2014.08.28 on commence aussi a parlé de la bd africaine et donc ...
WDF19/A0000.10894 2014.08.28 wikipedia ce prete parfaitement Ă ce genre de decryptage .
One text per line with <p> as sentence delimiter.
./build/bin/korapxmltool -t now /vol/corpora/DeReKo/current/KorAP/zip/*24.zip | pv > dach24.txtIf lemma annotations (morpho layer) are present alongside the base tokens, you can output lemmas instead of surface tokens with --lemma.
# Word2Vec style output with lemmas where available
./build/bin/korapxmltool --lemma -t w2v app/src/test/resources/goe.tree_tagger.zip | head -3
# NOW corpus style output with lemmas
./build/bin/korapxmltool --lemma -t now app/src/test/resources/goe.tree_tagger.zip | head -1If a lemma for a token is missing (_) the surface form is used as fallback.
--lemma-only: For-t w2vand-t now, skip loadingdata.xmland output only lemmas frommorpho.xml. This reduces memory and speeds up throughput.--sequential: Process entries inside each zip sequentially (zips can still run in parallel). Recommended forw2v/nowto keep locality and lower memory.- Parallel
w2v/nowruns schedule ZIPs in argument order and use a single bounded entry backlog across all open ZIPs. Completion and output order can still vary when multiple ZIPs run concurrently. Use--largest-firstto opt into size-descending scheduling when minimizing the low-parallelism tail matters more than corpus order. For reproducible server runs, set both--threadsand--zip-parallelismexplicitly. --exclude-zip-glob GLOB(repeatable): Skip zip basenames that match the glob (e.g.,--exclude-zip-glob 'w?d24.tree_tagger.zip').
Example for large NOW export with progress and exclusions:
KORAPXMLTOOL_XMX=64g KORAPXMLTOOL_MODELS_PATH=/data/models KORAPXMLTOOL_JAVA_OPTS="-XX:+UseG1GC -Djdk.util.zip.disableMemoryMapping=true -Djdk.util.zip.reuseInflater=true" \
./build/bin/korapxmltool -l info -j 100 --zip-parallelism 8 \
--lemma-only --sequential -t now \
--exclude-zip-glob 'w?d24.tree_tagger.zip' \
/vol/corpora/DeReKo/current/KorAP/zip/*24.tree_tagger.zip | pv > dach2024.lemma.txt
At INFO level the tool logs:
- The ZIP processing order with file sizes (argument order by default, or size-descending with
--largest-first). - For each zip: start message including its size and a completion line with cumulative progress, ETA and average MB/s.
Generate a tar archive containing gzipped Krill/KoralQuery JSON files across all provided foundries.
./build/bin/korapxmltool -t krill -D out/krill \
app/src/test/resources/wud24_sample.zip \
app/src/test/resources/wud24_sample.spacy.zip \
app/src/test/resources/wud24_sample.marmot-malt.zipThis writes out/krill/wud24_sample.krill.tar plus a log file. Add more annotated KorAP-XML zips (e.g., TreeTagger, CoreNLP) to merge their layers into the same Krill export; use --non-word-tokens if punctuation should stay in the token stream.
In addition to token and span annotations, text-level metadata can be supplied as
stand-off metadata: one <standOff> XML file per corpus that assigns metadata to
texts by their raw_text/@docid. This is useful for classifications that are produced
separately (e.g. Wikipedia topic domains) or for data that changes occasionally (e.g.
external links), without changing the source TEI files and re-running the corpus conversion.
Just list such files alongside the zips â they are auto-detected by content (root
element <standOff>), so no extra option is needed:
./build/bin/korapxmltool -t krill -D out/krill \
app/src/test/resources/rei_sample.zip \
app/src/test/resources/rei_sample.domains.meta.xmlEach <metadataLayer> becomes a Krill metadata field named after the layer's
xml:id: type="classification" layers become type:keywords fields, type="links"
layers become type:attachement fields. By default every category present in the file
is indexed, leaving the selection (e.g. top-k / threshold) to the tool that produced it.
A classification file is, for example, produced by piping the NOW output through a classifier:
./build/bin/korapxmltool -t now app/src/test/resources/rei_sample.zip \
| docker run --rm -i korap/wiki-taxonomy > rei_sample.wikiDomain.meta.xmlAn existing Krill tar can also be used as input and updated with new metadata
and/or annotation foundries â useful when the original KorAP-XML ZIPs are no longer
at hand, or when a single annotation foundry (e.g. an improved topic-domain
classification) must be fixed without re-running the whole conversion. Merge mode is
switched on simply by listing a .tar file among the inputs:
# Update/add a stand-off classification in an existing Krill tar
./build/bin/korapxmltool -t krill -D out/krill \
out/krill/rei_sample.krill.tar rei_sample.wikiDomain.meta.xml
# Replace (or add) the TreeTagger annotations in an existing Krill tar
./build/bin/korapxmltool -t krill -D out/krill \
out/krill/rei_sample.krill.tar app/src/test/resources/rei_sample.tree_tagger.zipThe result is written to a new tar (<name>.updated.krill.tar, or the path given
with -o); the input tar is never modified, so an interrupted run cannot damage
existing data. Properties of the merge:
- Texts not affected by the new inputs are copied through byte-identically, without even being decompressed; affected texts are patched and recompressed in parallel.
- Every foundry contained in the supplied annotation ZIPs is treated as authoritative: its existing annotations are replaced entirely; other foundries are left untouched. The patched texts are identical to what a full re-export with the same inputs would produce.
- Metadata fields from stand-off files,
<xenoData>and header ZIPs replace fields with the same key and are appended otherwise.creationDate/pubDateare only replaced when a new text-level header is supplied, so corpus-level headers cannot clobber per-text dates. - Texts present in the new inputs but missing from the tar are ignored with a
warning. The base tokenization of the tar cannot be changed:
data.xml/tokens.xml/structure.xmlentries are ignored as well. - Tars produced by korapxml2krill (Perl) are supported; untouched texts and annotations keep their exact original form.
You need to download the pre-trained MarMoT models from the MarMoT models repository.
You can specify the full path to the model, or set the KORAPXMLTOOL_MODELS_PATH environment variable to specify a default search directory:
# With full path
./build/bin/korapxmltool -t zip -T marmot:models/de.marmot app/src/test/resources/goe.zip
# With KORAPXMLTOOL_MODELS_PATH (searches in /data/models/ if model not found locally)
export KORAPXMLTOOL_MODELS_PATH=/data/models
./build/bin/korapxmltool -t zip -T marmot:de.marmot app/src/test/resources/goe.zip
# Without setting KORAPXMLTOOL_MODELS_PATH (searches current directory only)
./build/bin/korapxmltool -t zip -T marmot:models/de.marmot app/src/test/resources/goe.zipYou need to download the pre-trained OpenNLP models from the OpenNLP model download page or older models from the legacy OpenNLP models archive.
./build/bin/korapxmltool -t zip -T opennlp:/usr/local/kl/korap/Ingestion/lib/models/opennlp/de-pos-maxent.bin /tmp/zca24.zip(Requires Docker)
./build/bin/korapxmltool -T treetagger:german -t zip app/src/test/resources/wdf19.zipSee TreeTagger Docker Image with CoNLL-U Support.
(Requires Docker)
./build/bin/korapxmltool -j 1 -T spacy ./app/src/test/resources/goe.zip | less./build/bin/korapxmltool -P spacy -t zip ./app/src/test/resources/goe.zipDownload the Stanford CoreNLP v3.X POS tagger and constituency parser models (e.g., german-fast.tagger and germanSR.ser.gz) into libs/.
./build/bin/korapxmltool -t zip -D out \
-T corenlp:libs/german-fast.tagger \
-P corenlp:libs/germanSR.ser.gz \
app/src/test/resources/wud24_sample.zipThe resulting out/wud24_sample.corenlp.zip contains corenlp/morpho.xml and corenlp/constituency.xml alongside the base tokens.
You need to download the pre-trained MaltParser models from the MaltParser model repository. Note that parsers take POS tagged input.
./build/bin/korapxmltool -t zip -j2 -P malt:german.mco goe.tree_tagger.zip./build/bin/korapxmltool -t zip -T marmot:models/de.marmot -P malt:german.mco goe.zipAuthor:
Copyright (c) 2024-2026, Leibniz Institute for the German Language, Mannheim, Germany
This package is developed as part of the KorAP Corpus Analysis Platform at the Leibniz Institute for German Language (IDS).
It is published under the GNU General Public License, Version 3, 29 June 2007.
Contributions are very welcome!
Your contributions should ideally be committed via our Gerrit server to facilitate reviewing ( see Gerrit Code Review - A Quick Introduction if you are not familiar with Gerrit). However, we are also happy to accept comments and pull requests via GitHub.