Cette page n'est disponible qu'en anglais !
Conversion scripts for coreference annotation formats (corefconversion)
The corefconversion GitHub repository contains conversion scripts for coreference. The main formats we are dealing with here (conll, jsonlines, text) are described at the end of this document.
download code view github repo
On this page:
The jsonlines2text.py script
Script to convert from a jsonlines file to a text representation of coreference annotation. The output is html. Mentions are surrounded by brackets. Coreference chains are represented by colors (each chain has a specific color) and, if requested by a switch, an index (1, 2, 3...). Singletons may be hidden or shown in a specific color (gray by default), without any index.
If your jsonlines file contains several documents, you may show the document name by using the --heading option.
In any case, use the -h and --help switches to get a detailed list of options.
Here are some example (command then illustration):
(1) Color without index:
(2) Color with index:
(Note: indices don't start at 1 in the image becaue it's not the beginning of the text.)
(3) Hide singletons:
(4) No color (cm stands for color manager):
(5) Using common html colors (more constrast, but fewer available colors, so several chains may have the same color):
(6) Limiting the output to the N first tokens:
The jsonlines2conll.py script
Script to convert a jsonlines file to a CoNLL file. Use the -h and --help switches to get detailed help on the options.
Example command (output uses spaces):
#begin document (ge/articleswiki_singe.xml); part 000
Singe (0)
Les (0
singes 0)
sont -
des (0
mammifères -
de -
l' (1
ordre -
des -
de -
les (2
primates 1)|2)
...
#end document
Example command (merging coreference information with an existing conll file, for example to add predicted coreference):
#begin document (ge/articleswiki_singe.xml); part 000
1 Singe Singe NOUN ...
1 Les le DET ...
2 singes singe NOUN ...
3 sont être AUX ...
4 des un DET ...
5 mammifères mammifère NOUN ...
6 de de ADP ...
7 l' le DET ...
8 ordre ordre NOUN ...
9-10 des _ _ ...
9 de de ADP ...
10 les le DET ...
11 primates primate NOUN ...
...
#end document
Example command (merging + output uses tabulation):
The conll2jsonlines.py script
Script to convert a conll formatted file to a jsonlines formatted file. Use the -h and --help switches to get detailed help on the options.
For example, to convert from the original CoNLL2012 format into jsonlines format:
To convert from the StanfordNLP format into jsonlines format:
python3 conll2jsonlines.py \
--skip-singletons \
--skip-empty-documents \
--tab \
--ignore-double-indices 0 \
--token-col 1 \
--speaker-col "_" \
--no-coref \
INPUT_FILE \
OUTPUT_FILETo convert from the Democrat corpus in CoNLL format (with a column for paragraphs at position 11):
python3 conll2jsonlines.py \
--tab \
--ignore-double-indices 0 \
--token-col 1 \
--speaker-col "_" \
--par-col 11 \
testing/singe.conll \
testing/singe.jsonlinesNote that you may have to change document keys in the CoNLL files before running this script if you want to transform them.
Output sample:
{
"doc_key": "(ge/articleswiki_singe.xml); part 000",
"clusters": [[[0, 0], [1, 2], [4, 12]], [[7, 12]], [[11, 12]]],
"sentences": [["Singe"],
["Les", "singes", "sont", "des", "mammif\u00e8res", "de",
"l'", "ordre", "des", "de", "les", "primates", "."]],
"speakers": [["_"],
["_", "_", "_", "_", "_", "_",
"_", "_", "_", "_", "_", "_", "_"]],
"paragraphs": [[0, 0], [1, 13]]
}
text2jsonlines.py
Script to convert a plain text to a jsonlines format (used for example for cofr).
It tokenizes the text with StanfordNLP. You need to install StanfordNLP via pip and then load the models, for example for French models (use "en" for English models):
Notes:
- the doc key is the concatenation of
--genreand the file path, - speaker data are left blank ("_")
Usage:
python3 text2jsonlines.py <plain.txt> -o <output.jsonlines>
Choose the language with the --lang option (en by default, use fr for French).
Example with the sentence "I eat an apple.":
{
"doc_key": "ge:input.txt",
"sentences": [["I", "eat", "an", "apple", "."]],
"speakers": [["_", "_", "_", "_", "_"]],
"clusters": [],
"pos": [["PRON", "VERB", "DET", "NOUN", "PUNCT"]],
"paragraphs": [[0, 4]]
}
jsonlines2tei.py
Script to convert the jsonlines format into a TEI-URS format used by softwares such as TXM. See the jsonlines2tei repository.
Function library conll_transform.py
Module containing several function to manipulate conll data:
read_files: Read one or several conll files and return a dictionary of documents.read_file: Read a conll file and return dictionary of documents.write_file: Write a conll file.compute_mentions: Compute mentions from the raw last column of the conll file.compute_chains: Compute and return the chains from the conll data.sentpos2textpos: Transform mentions[SENT, START, STOP]to[TEXT_START, TEXT_STOP].textpos2sentpos: Transform mentions[TEXT_START, TEXT_STOP]to[SENT, START, STOP].write_chains: Convert a list of chains to a conll coreference column.replace_coref_col: Replace the last column oftar_docsby the last column ofsrc_docs.remove_singletons: Remove the singletons of the conll fileinfpath, and write the version without singleton in the conll fileoutfpath.filter_pos: Filter mentions that have POS in unwanted_pos, return a new mention list.check_no_duplicate_mentions: Return True if there is no duplicate mentions.merge_boundaries: Add the mentions ofboundary_docstocoref_docsif they don't already exist, as singletons.remove_col: Remove columns from all tokens in docs.write_mentions: Opposite forcompute_mentions(). Write the last column insent.compare_coref_cols: Build a conll file that merge the corefcols of several other files.to_corefcol: Write the conll fileoutfpathwith just the last column (coref) of the conll fileinfpath.get_conll_2012_key_pattern: Return a compiled pattern object to match conll2012 key format.merge_amalgams: Add amalgams in documents from where they have been removed.
Main formats used in automatic coreference resolution
The CoNLL format is a tabular format: each token is on a separate line and annotation for the token are on separate column. Document boundaries are indicated by specific marks, and sentence separation by a white line.
Here is an example:
#begin document <name of the document>
1 Les le DET
2 singes singe NOUN
3 sont être AUX
4 des un DET
5 mammifères mammifère NOUN
...
1 Bien bien ADV
2 que que SCONJ
3 leur son DET
4 ressemblance ressemblance NOUN
5 avec avec ADP
6 l' le DET
7 Homme homme NOUN
...
#end document
Column separator (spaces or tabulation), number and content vary according to specification (CoNLL-2012, CoNLL-U, CoNLL-X, etc.).
The jsonlines format stores data for several texts (a corpus). Each line is a valid json document, as follows:
{
"clusters": [],
"doc_key": "nw:docname",
"sentences": [["This", "is", "the", "first", "sentence", "."],
["This", "is", "the", "second", "."]],
"speakers": [["spk1", "spk1", "spk1", "spk1", "spk1", "spk1"],
["spk2", "spk2", "spk2", "spk2", "spk2"]]
"pos": [["DET", "V", "DET", "ADJ", "NOUN", "PUNCT"],
["DET", "V", "DET", "ADJ", "PUNCT"]],
...
}
It is used for some coreference resolution systems, such as:
- https://github.com/kentonl/e2e-coref (English)
- https://github.com/kkjawz/coref-ee (English)
- https://github.com/boberle/cofr (French)