SeqScore provides scoring for named entity recognition and other chunking tasks evaluated over sequence labels.
SeqScore is maintained by the BLT Lab at Brandeis University. Please open an issue if you find incorrect behavior or features you would like to see added. Due to the risk of introducing regressions or incorrect scoring behavior, we generally do not accept pull requests. Please do not open a pull request unless you are asked to do so by a maintainer in an issue.
To install the latest official release of SeqScore, run: pip install seqscore.
This will install the package and add the command seqscore in your Python
environment.
SeqScore requires Python 3.7 or higher. It is tested on Python 3.7, 3.8, 3.9, 3.10, and 3.11.
SeqScore is distributed under the MIT License.
If you use SeqScore, please cite SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation.
BibTeX:
@inproceedings{palen-michel-etal-2021-seqscore,
title = "{S}eq{S}core: Addressing Barriers to Reproducible Named Entity Recognition Evaluation",
author = "Palen-Michel, Chester and
Holley, Nolan and
Lignos, Constantine",
booktitle = "Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eval4nlp-1.5",
pages = "40--50",
}
For a list of commands, run seqscore --help:
$ seqscore --help
Usage: seqscore [OPTIONS] COMMAND [ARGS]...
Options:
--version Show the version and exit.
--help Show this message and exit.
Commands:
convert
count
repair
score
summarize
validate
The most common application of SeqScore is scoring CoNLL-format NER predictions. Let's assume you have two files, one containing the correct labels (annotation) and the other containing the predictions (system output).
The correct labels are in the file samples/reference.bio:
This O
is O
a O
sentence O
. O
University B-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O
The predictions are in the file samples/predicted.bio:
This O
is O
a O
sentence O
. O
University B-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West B-LOC
Philadelphia B-LOC
, O
Pennsylvania B-LOC
. O
To score the predictions, run:
seqscore score --labels BIO --reference samples/reference.bio samples/predicted.bio
| Type | Precision | Recall | F1 | Reference | Predicted | Correct |
|--------|-------------|----------|--------|-------------|-------------|-----------|
| ALL | 50.00 | 66.67 | 57.14 | 3 | 4 | 2 |
| LOC | 33.33 | 50.00 | 40.00 | 2 | 3 | 1 |
| ORG | 100.00 | 100.00 | 100.00 | 1 | 1 | 1 |
A few things to note:
- The reference file must be specified with the
--referenceflag. - The chunk encoding (BIO, BIOES, etc.) must be specified using the
--labelsflag. - Both files need to use the same chunk encoding. If you have
files that use different chunk encodings, use the
convertcommand. - You can get output in different formats using the
--score-formatflag. Using--score-format delimwill produce tab-delimited output. In the delimited format, you can specify the--full-precisionflag to output higher numerical precision. - In the default (pretty) output format, numbers are rounded "half up"
at two decimal places. In other words, 57.124 will round to 57.12,
and 57.125 will round to 57.13. This is different than the "half even"
rounding used by
conllevaland other libraries that rely onprintfbehavior for rounding. Half up rounding is used as it is more likely to match the rounding a user would perform if shown three decimal places. If you requestconllevaloutput format, the same rounding used byconllevalwill be used.
The above scoring command will work for files that do not have any invalid transitions, that is, those that perfectly follow what the encoding allows. However, consider this BIO-encoded file, samples/invalid.bio:
This O
is O
a O
sentence O
. O
University I-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O
Note that the token University has the label I-ORG, but there is
no preceding B-ORG. If we score it as before with
seqscore score --labels BIO --reference samples/reference.bio samples/invalid.bio,
scoring will fail:
seqscore.encoding.EncodingError: Stopping due to validation errors in invalid.bio:
Invalid transition 'O' -> 'I-ORG' for token 'University' on line 7
To score output with invalid transitions, we need to specify a repair
method which can correct them. We can tell SeqScore to use the same
approach that conlleval uses (which we refer to as "begin" repair in our
paper):
seqscore score --labels BIO --repair-method conlleval --reference samples/reference.bio samples/invalid.bio:
Validation errors in sequence at line 7 of invalid.bio:
Invalid transition 'O' -> 'I-ORG' for token 'University' on line 7
Used method conlleval to repair:
Old: ('I-ORG', 'I-ORG', 'I-ORG', 'O', 'O', 'B-LOC', 'I-LOC', 'O', 'B-LOC', 'O')
New: ('B-ORG', 'I-ORG', 'I-ORG', 'O', 'O', 'B-LOC', 'I-LOC', 'O', 'B-LOC', 'O')
| Type | Precision | Recall | F1 | Reference | Predicted | Correct |
|--------|-------------|----------|--------|-------------|-------------|-----------|
| ALL | 100.00 | 100.00 | 100.00 | 3 | 3 | 3 |
| LOC | 100.00 | 100.00 | 100.00 | 2 | 2 | 2 |
| ORG | 100.00 | 100.00 | 100.00 | 1 | 1 | 1 |
You can use the -q flag to suppress the logging of all of the repairs
applied. For example, running the command
seqscore score -q --labels BIO --repair-method conlleval --reference samples/reference.bio samples/invalid.bio
will hide the repairs:
| Type | Precision | Recall | F1 | Reference | Predicted | Correct |
|--------|-------------|----------|--------|-------------|-------------|-----------|
| ALL | 100.00 | 100.00 | 100.00 | 3 | 3 | 3 |
| LOC | 100.00 | 100.00 | 100.00 | 2 | 2 | 2 |
| ORG | 100.00 | 100.00 | 100.00 | 1 | 1 | 1 |
You may want to also explore the discard repair, which can
produce higher scores for output from models without a CRF/constrained
decoding as they are more likely to produce invalid transitions.
SeqScore can also display all errors (false positives and false negatives)
encountered in scoring using the --error-counts flag. For example, running the
command
seqscore score --labels BIO --error-counts --reference samples/reference.bio samples/predicted.bio
will produce the following output:
| Count | Error | Type | Tokens |
|---------|---------|--------|-------------------|
| 1 | FP | LOC | Philadelphia |
| 1 | FP | LOC | West |
| 1 | FN | LOC | West Philadelphia |
The output shows that the system produced two false positives and missed one
mention in the reference (false negative). The most frequent errors appear at
the top. The --error-counts flag can be combined with --score-format delim
to write a delimited table that can be read as a spreadsheet.
To check if a file has any invalid transitions, we can run
seqscore validate --labels BIO samples/reference.bio:
No errors found in 0 tokens, 2 sequences, and 1 documents in reference.bio
For the example of the samples/invalid.bio, we can run
seqscore validate --labels BIO samples/invalid.bio:
Encountered 1 errors in 1 tokens, 2 sequences, and 1 documents in invalid.bio
Invalid transition 'O' -> 'I-ORG' for token 'University' on line 7
We can convert a file from one chunk encoding to another. For example,
seqscore convert --input-labels BIO --output-labels BIOES samples/reference.bio samples/reference.bioes
will read samples/reference.bio in BIO
encoding and write the BIOES-converted file to samples/reference.bioes:
This O
is O
a O
sentence O
. O
University B-ORG
of I-ORG
Pennsylvania E-ORG
is O
in O
West B-LOC
Philadelphia E-LOC
, O
Pennsylvania S-LOC
. O
We can get a list of available chunk encodings by running seqscore convert --help:
Usage: seqscore convert [OPTIONS] FILE OUTPUT_FILE
Options:
--file-encoding TEXT [default: UTF-8]
--ignore-comment-lines
--ignore-document-boundaries / --use-document-boundaries
--output-delim TEXT [default: space]
--input-labels [BIO|BIOES|BILOU|BMES|BMEOW|IO|IOB]
[required]
--output-labels [BIO|BIOES|BILOU|BMES|BMEOW|IO|IOB]
[required]
--help Show this message and exit.
We can also apply repair methods to a file, creating an output file
with only valid transitions. For example, we can run
seqscore repair --labels BIO --repair-method conlleval samples/invalid.bio samples/invalid_repair_conlleval.bio,
which will apply the conlleval repair method to the
samples/invalid.bio and write the repaired
labels to
samples/invalid_repair_conlleval.bio:
This O
is O
a O
sentence O
. O
University B-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O
If we want to apply the discard repair method, we can run
seqscore repair --labels BIO --repair-method discard samples/invalid.bio samples/invalid_repair_discard.bio
and the output will be written to samples/invalid_repair_discard.bio:
This O
is O
a O
sentence O
. O
University O
of O
Pennsylvania O
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O
Repairing the file before performing other operations is available in the
count and summarize subcommands.
The summarize subcommand can produce counts of the types of chunks
in the input file. For example, if we run
seqscore summarize --labels BIO samples/reference.bio
we get the following output:
File 'samples/reference.bio' contains 1 document(s) with the following mentions:
| Entity Type | Count |
|---------------|---------|
| LOC | 2 |
| ORG | 1 |
If the quiet (-q) flag is provided, the first line giving the filename
and document count is not printed.
The count subcommand can produce the counts of chunks in the input
file. Unlike summarize, it counts chunk-type pairs, not just types.
For example, if we run
seqscore count --labels BIO samples/reference.bio counts.csv,
tab-delimited counts would be written to counts.csv as follows:
1 ORG University of Pennsylvania
1 LOC West Philadelphia
1 LOC Pennsylvania
The process subcommand can remove entity types from a file or map them to
other types. Removing types can be performed by specifying one of --keep-types
or --remove-types.
For example, if we only wanted to keep the ORG type, we could run:
seqscore process --labels BIO --keep-types ORG samples/reference.bio samples/keep_ORG.bio,
and the following output will be written to samples/keep_ORG.bio:
This O
is O
a O
sentence O
. O
University B-ORG
of I-ORG
Pennsylvania I-ORG
is O
in O
West O
Philadelphia O
, O
Pennsylvania O
. O
You can also keep multiple types by specifying a comma-separated list of types:
--keep-types LOC,ORG.
Instead of specifying which types to keep, we can also specify which types to
remove using --remove-types. For example, if we wanted to remove only the
ORG type, we could run:
seqscore process --labels BIO --remove-types ORG samples/reference.bio samples/remove_ORG.bio,
and the following output will be written to samples/remove_ORG.bio:
This O
is O
a O
sentence O
. O
University O
of O
Pennsylvania O
is O
in O
West B-LOC
Philadelphia I-LOC
, O
Pennsylvania B-LOC
. O
As with keep, you can specify multiple tags to remove, for example
--remove-types LOC,ORG.
The --type-map argument allows you to specify a JSON file that specifies a
mapping between types and other types. Suppose you want to collapse several
types into a more generic NAME type. In that case, the type map would be
specified as follows:
{
"NAME": ["LOC", "ORG"]
}
The type map must be a JSON dictionary. The keys are the types to be mapped to, while the value for each key is a list of types to be mapped from. Note that the value must always be a list, even if it would only contain one element.
We can apply the above type map to a file using the following command:
seqscore process --labels BIO --type-map samples/type_map_NAME.json samples/reference.bio samples/all_NAME.bio,
resulting in this output:
This O
is O
a O
sentence O
. O
University B-NAME
of I-NAME
Pennsylvania I-NAME
is O
in O
West B-NAME
Philadelphia I-NAME
, O
Pennsylvania B-NAME
. O
At this time, SeqScore intentionally does not support the "merged"
format used by conlleval where each line contains a token, correct
tag, and predicted tag:
University B-ORG B-ORG
of I-ORG I-ORG
Pennsylvania I-ORG I-ORG
is O O
in O O
West B-LOC B-LOC
Philadelphia I-LOC B-LOC
, O O
Pennsylvania B-LOC B-LOC
. O O
We do not support this format because we have found that creating predictions in this format is a common source of errors in scoring pipelines.
The following instructions are for the project maintainers only.
For development, check out the dev branch (latest, but less tested
than main).
To install from a clone of this repository, use:
pip install -e .
- Create an environment:
conda create -y -n seqscore python=3.7 - Activate the environment:
conda activate seqscore - Install seqscore:
pip install -e . - Install development dependencies:
pip install -r requirements.txt
SeqScore was developed by the BLT Lab at Brandeis University under the direction of PI and and lead developer Constantine Lignos. Chester Palen-Michel and Nolan Holley contributed to its development. Gordon Dou, Maya Kruse, and Andrew Rueda gave feedback on its features and assisted in README writing.